Tumor microenvironment-based methods for assessing car-t and other immunotherapies

ABSTRACT

Aspects of the disclosure relate to methods for determining whether or a subject is likely to respond to certain adoptive cell therapies (e.g., chimeric antigen receptor (CAR) T-cell therapy, etc.). In some embodiments, the methods comprise the steps of identifying a subject as having a tumor microenvironment (TME) type based upon a molecular-functional (MF) expression signature of the subject, and determining whether or not the subject is likely to respond to a chimeric antigen receptor (CAR) T-cell therapy based upon the TME type. In some embodiments, the methods comprise determining the lymphoma microenvironment (LME) type of a lymphoma (e.g., Diffuse Large B cell lymphoma (DLBCL)) subject and identifying the subjects prognosis based upon the LME type determination.

RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. 119(e) of the filingdate of U.S. provisional Application Ser. No. 63/128,426, filed Dec. 21,2020, and U.S. provisional Application Ser. No. 63/048,378, filed Jul.6, 2020, the entire contents of each of which are incorporated herein byreference.

BACKGROUND

Adoptive cell transfer is a targeted immune cell therapy that ofteninvolves engineering a patients immune cells to recognize and attack hisor her tumor(s). Immune cells collected from a patients blood can begenetically engineered to express receptors on the immune cell surface,which permits recognition by the immune cells of specific ligandproteins (e.g., antigens) expressed on a tumor cell surface. Invitro-expanded populations of these genetically engineered immune cellsare infused back into the patient, the immune cells multiply in thepatients body and, with guidance from the engineered receptors,recognize and kill cancer cells that harbor the surface antigen.

SUMMARY

Aspects of the disclosure relate to methods for determining whether ornot a subject is likely to respond to certain adoptive cell therapies(e.g., chimeric antigen receptor (CAR) T-cell therapy, etc.) and/orother immunotherapies. The disclosure is based, in part, on therecognition that cancer cells (e.g., solid tumor cells, hematologicalcancer cells, etc.) obtained from a subject may be used to identify atumor microenvironment (TME) type of the subject (e.g., a blood canceror lymphoma TME type, solid tumor cancer TME type, etc.), which isindicative of whether or not the subject is likely to respond toadoptive cell therapies, for example treatment with chimeric antigenreceptor (CAR) T-cell therapy.

The inventors have recognized that gene expression data of a sampleobtained from a cancer patient can be processed to produce certainmolecular functional signatures (for example molecular functionalexpression signatures (MFES) and lymphoma microenvironment (LME)signatures) that reflect the biological processes occurring in the tumormicroenvironment (TME) of the subject. In some embodiments, thesignatures are produced by processing gene expression data for aplurality of gene groups, where each gene group comprises genes that areinvolved in the particular biological process encompassed by that genegroup (e.g., genes involved in angiogenesis may be part of anAngiogenesis gene group). Processing gene expression data in this way,across gene groups that underlie several different biological processes,provides a snapshot of the tumor microenvironment (TME) of the subject.While previous methods of assessing biomarkers to identify appropriatetherapies have been described, the inventors believe that thecombinations of gene groups and gene group genes utilized in theinvention are novel and unconventional because they allowcharacterization of the TME as a whole instead of as a collection ofdiscreet biological processes.

Furthermore, the inventors have discovered that across certain cancers,for example blood cancers or solid cancers, or within certain cancers(e.g., lymphomas), these signatures can be categorized into four maintypes which are indicative of a subjects 1) prognosis (e.g.,progression-free survival at 24-months; “PFS24”), and/or 2) likelihoodof responding to a particular therapeutic intervention (e.g., adoptivecell transfer therapies, such as CAR-T therapy). Without wishing to bebound by any particular theory, the predictive power of the tumormicroenvironment (TME) typing methods described herein relates to theconnection between the signatures developed by the inventors andunderlying tumor microenvironment biology of the subject.

The methods described herein offer several advantages and improvementsto currently existing prognosis and therapeutic agent selectiontechniques. First, because the signatures and TME types described hereinreflect the underlying TME biology of the subject, methods describedherein provide physicians with increased confidence in prescribing CAR-Ttherapies to certain populations of patients that may not have a highresponse rate to first-line therapeutics (e.g., rituximab). Second,classification of patients by TME type may improve clinical trial designand efficiency by allowing selection of patients who are likely torespond to CAR-T therapy, and excluding subjects having TME typesindicative of a lower response to CAR-T therapy.

Aspects of the disclosure relate to methods, systems, computer-readablestorage media, and graphical user interfaces (GUIs) that can be used fordetermining whether or not a subject is likely to respond to an adoptivecell transfer therapy. In some aspects, the disclosure provides a methodfor determining whether or not a subject is likely to respond to anadoptive cell transfer therapy (e.g., chimeric antigen receptor (CAR)T-cell therapy), comprising: using at least one computer hardwareprocessor to perform: obtaining sequencing data for a subject having,suspected of having, or at risk of having a solid tumor cancer or ablood cancer; determining a molecular-functional expression signature(MFES) for the subject using the sequencing data; identifying, fromamong tumor microenvironment (TME) types, a TME type associated with thecancer using the determined MF expression signature of the subject; anddetermining whether the subject is likely to respond to the adoptivecell transfer therapy based at least in part on the identified TME type.

In some embodiments, adoptive cell transfer therapy is a CAR T-celltherapy.

In some embodiments, a subject is a human.

In some embodiments, sequencing data is obtained from one or morebiological samples obtained from the subject. In some embodiments, thebiological sample comprises a blood sample or tissue sample. In someembodiments, a tissue sample comprises a tumor tissue sample.

In some embodiments, the sequencing data comprises RNA sequencing data.In some embodiments, the sequencing data comprises at least 5 kb of DNA.In some embodiments, the sequencing data comprises at least 5 kb of RNA.

In some embodiments, determining the molecular-functional (MF)expression signature comprises processing the sequencing data to obtaingene expression data.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determinegene group expression scores for at least one (e.g., 1, 2, 3, 4, 5, ormore) of the following gene groups: Lymphatic endothelium (LEC),Angiogenesis (VEC), Cancer-associated fibroblasts (CAF), Fibroblasticreticular cells (FRC), Matrix (ECM), Matrix Remodeling (ECM remodeling),Granulocyte traffic, Protumor cytokines (IS cytokines), FollicularDendritic Cells (FDC), Macrophages, M1 signature (activated M1),Effector cell traffic (T cell traffic), Major histocompatibility complexII (MHC-II), Major histocompatibility complex I (MHC-I), Follicular Bhelper T cells (TFH), Regulatory T cells (Treg), T cells (TIL),Checkpoint inhibition (IS checkpoints), Natural Killer Cells (NK cells),B cell traffic, Benign B cells (B cells), Tumor proliferation rate (cellproliferation), Nuclear factor kappa B (NFkB), Phosphoinositide 3-kinase(PI3K), and p53.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for one or more genes (e.g., 1, 2, 3, 4, 5,or more) of the following gene groups using gene expression data fromone or more genes (e.g., 1, 2, 3, 4, 5, or more) of the respectivefollowing sets of genes: Lymphatic endothelium (LEC): JAM3, PPP1R13B,CXCL12, PDPN, CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, andJAM2; Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF,CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, and ANGPT2;Cancer-associated fibroblasts (CAF): COL1A1, WP2, LGALS1, WP7, LRP1,CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1,WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, MMP12, MFAP5, MMP1,COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2, and TGFB2;Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E, VIM,PDPN, THY1, DES, VCAM1, PTGS2, and LTBR; Matrix (ECM): COL1A1, COL3A1,LGALS7, FN1, VTN, COL1A2, and COL4A1; Matrix Remodeling (ECMremodeling): TIMP1, TIMP2, WP2, WP9, and CA9; Granulocyte traffic:KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2;Protumor cytokines (IS cytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8,IL22, and IL10; Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A, LTBR,FDCSP, CLU, PRNP, and BST1; Macrophages: IL10, MSR1, ARG1, CSF1R, CD163,MRC1, and CSF1; M1 signature (activated M1): TNF, NOS2, IL1B, andCMKLR1; Effector cell traffic (T cell traffic): CXCL11, CXCL10, CXCL9,CXCR3, CX3CL1, CCL5, and CX3CR1; Major histocompatibility complex II(MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA,HLA-DRB1, and HLA-DMB; Major histocompatibility complex I (MHC-I): TAP1,HLA-C, B2M, HLA-B, HLA-A, and TAP2; Follicular B helper T cells (TFH):CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, and ICOS;Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, andTNFRSF18; T cells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E,TRBC1, TRAC, and CD3G; Checkpoint inhibition (IS checkpoints): CTLA4,HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, and LAG3; Natural KillerCells (NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG,GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1; Bcell traffic: CXCL13, CXCR5, CCR6, and CCL20; Benign B cells (B cells):CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, and FCRL5; and Tumor proliferation rate (cellproliferation): MCM6, AURKB, ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1,MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, and BUB1.

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Majorhistocompatibility complex I (MHC-I).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Majorhistocompatibility complex II. (MHC-II).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Effectorcell traffic (T cell traffic).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of RegulatoryT cells (Treg).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of M1signature (activated M1).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Checkpointinhibition (IS checkpoints).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of T cells(TIL).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofMacrophages.

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofCancer-associated fibroblasts (CAF).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Matrix(ECM).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of MatrixRemodeling (ECM remodeling).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofAngiogenesis (VEC).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Tumorproliferation rate (cell proliferation).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of EMTsignature.

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Lymphaticendothelium (LEC).

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Lymphatic endothelium (LEC) genegroup using one or more (e.g., 1, 2, 3, 4, 5, or more) genes selectedfrom: JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21, FOXC2, EDNRB,LYVE1, PROX1, SOX18, and JAM2.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Angiogenesis (VEC) gene group usingone or more (e.g., 1, 2, 3, 4, 5, or more) genes selected from: CDH5,PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA,KDR, VEGFB, and ANGPT2.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Cancer-associated fibroblasts (CAF)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)Cancer-associated fibroblasts genes selected from: COL1A1, WP2, LGALS1,WP7, LRP1, CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1, COL1A2,COL5A1, COL6A1, WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, WP12,MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2, andTGFB2.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Fibroblastic reticular cells (FRC)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more) genesselected from: PDGFRA, ACTA2, ICAM1, NT5E, VIM, PDPN, THY1, DES, VCAM1,PTGS2, and LTBR.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Matrix (ECM) gene group using one ormore (e.g., 1, 2, 3, 4, 5, or more) genes selected from: COL1A1, COL3A1,LGALS7, FN1, VTN, COL1A2, and COL4A1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Matrix Remodeling (ECM remodeling)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more) genesselected from: TIMP1, TIMP2, MMP2, MMP9, and CA9.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Granulocyte traffic gene group usingone or more (e.g., 1, 2, 3, 4, 5, or more) genes selected from: KITLG,CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Protumor cytokines (IS cytokines)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more) genesselected from: CCL4, IL6, TNFSF13B, MIF, CXCL8, IL22, and IL10.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Follicular Dendritic Cells (FDC)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more) genesselected from: PDPN, TNFRSF1A, LTBR, FDCSP, CLU, PRNP, and BST1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Macrophages gene group using one ormore (e.g., 1, 2, 3, 4, 5, or more) genes selected from: IL10, MSR1,ARG1, CSF1R, CD163, MRC1, and CSF1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the M1 signature (activated M1) genegroup using one or more (e.g., 1, 2, 3, 4, or more) genes selected from:TNF, NOS2, IL1B, and CMKLR1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Effector cell traffic (T celltraffic) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: CXCL11, CXCL10, CXCL9, CXCR3, CX3CL1, CCL5, andCX3CR1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Major histocompatibility complex II(MHC-II) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1,HLA-DMA, HLA-DRB1, and HLA-DMB.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Major histocompatibility complex I(MHC-I) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: TAP1, HLA-C, B2M, HLA-B, HLA-A, and TAP2.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Follicular B helper T cells (TFH)gene group using one or more (e.g., 1, 2, 3, 4, 5, or more) genesselected from: CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21,and ICOS.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Regulatory T cells (Treg) gene groupusing one or more (e.g., 1, 2, 3, 4, 5, or more) genes selected from:CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, and TNFRSF18.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the T cells (TIL) gene group using oneor more (e.g., 1, 2, 3, 4, 5, or more) genes selected from: CD3D, TRAT1,TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC, and CD3G.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Checkpoint inhibition (IScheckpoints) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: CTLA4, HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2,and LAG3.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Natural Killer Cells (NK cells) genegroup using one or more (e.g., 1, 2, 3, 4, 5, or more) genes selectedfrom: SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG, GNLY, NCR1,CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the B cell traffic gene group using oneor more (e.g., 1, 2, 3, 4, 5, or more) genes selected from: CXCL13,CXCR5, CCR6, and CCL20.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Benign B cells (B cells) gene groupusing one or more (e.g., 1, 2, 3, 4, 5, or more) genes selected from:CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, and FCRL5.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determine agene group expression score for the Tumor proliferation rate (cellproliferation) gene group using one or more (e.g., 1, 2, 3, 4, 5, ormore) genes selected from: MCM6, AURKB, ESCO2, CCNB1, AURKA, MKI67,CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, and BUB1.

In some embodiments, determining the molecular-functional (MF)expression signature comprises using the sequencing data to determinegene group expression scores for each of the genes of each of thefollowing gene groups using gene expression data from each gene of therespective following sets of genes: Lymphatic endothelium (LEC): JAM3,PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1,SOX18, and JAM2; Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC,CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, and ANGPT2;Cancer-associated fibroblasts (CAF): COL1A1, WP2, LGALS1, WP7, LRP1,CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1,WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, MMP12, MFAP5, MMP1,COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2, and TGFB2;Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E, VIM,PDPN, THY1, DES, VCAM1, PTGS2, and LTBR; Matrix (ECM): COL1A1, COL3A1,LGALS7, FN1, VTN, COL1A2, and COL4A1; Matrix Remodeling (ECMremodeling): TIMP1, TIMP2, WP2, WP9, and CA9; Granulocyte traffic:KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2;Protumor cytokines (IS cytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8,IL22, and IL10; Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A, LTBR,FDCSP, CLU, PRNP, and BST1; Macrophages: IL10, MSR1, ARG1, CSF1R, CD163,MRC1, and CSF1; M1 signature (activated M1): TNF, NOS2, IL1B, andCMKLR1; Effector cell traffic (T cell traffic): CXCL11, CXCL10, CXCL9,CXCR3, CX3CL1, CCL5, and CX3CR1; Major histocompatibility complex II(MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA,HLA-DRB1, and HLA-DMB; Major histocompatibility complex I (MHC-I): TAP1,HLA-C, B2M, HLA-B, HLA-A, and TAP2; Follicular B helper T cells (TFH):CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, and ICOS;Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, andTNFRSF18; T cells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E,TRBC1, TRAC, and CD3G; Checkpoint inhibition (IS checkpoints): CTLA4,HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, and LAG3; Natural KillerCells (NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG,GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1; Bcell traffic: CXCL13, CXCR5, CCR6, and CCL20; Benign B cells (B cells):CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, and FCRL5; and Tumor proliferation rate (cellproliferation): MCM6, AURKB, ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1,MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, and BUB1. In some embodiments,determining gene group expression scores for each of the genes comprisesdetermining the gene expression data that is available. For example, theavailable gene expression data may include all genes in the gene sets asdisclosed herein. In some embodiments, the available gene expressiondata may not include all genes in the gene sets as disclosed herein.

In some embodiments, a tumor microenvironment (TME) type associated withthe cancer (e.g., a blood cancer or lymphoma, or a solid tumor cancer)is selected from type A, type B, type C, and type D.

In some embodiments, identifying the TME type comprises associating theMFES of the subject with a MFES cluster previously determined that isselected from a type A MFES cluster, a type B MFES cluster, a type CMFES cluster, and a type D MFES cluster.

In some embodiments, the adoptive cell transfer therapy is a CAR T-celltherapy, the subject has a blood cancer and the determining whether thesubject is likely to respond to CAR T-cell therapy comprises:determining that the subject is not likely to respond to CAR T-cellmonotherapy if the identified tumor type is blood cancer or lymphomatype A; determining that the subject is likely to respond to CAR T-cellmonotherapy if the identified tumor type is blood cancer or lymphomatype B; determining that the subject is not likely to respond to CART-cell monotherapy if the identified tumor type is blood cancer orlymphoma type C; or determining that the subject is not likely torespond to CAR T-cell monotherapy if the identified tumor type is bloodcancer or lymphoma type D.

In some embodiments, the adoptive cell transfer therapy is a CAR T-celltherapy, a subject has a solid tumor cancer and the determining whetherthe subject is likely to respond to CAR T-cell therapy comprises:determining that the subject is not likely to respond to CAR T-cellmonotherapy if the identified tumor type is solid tumor cancer type A;determining that the subject is likely to respond to CAR T-cellmonotherapy if the identified tumor type is solid tumor cancer type B;determining that the subject is not likely to respond to CAR T-cellmonotherapy if the identified tumor type is solid tumor cancer type C;or determining that the subject is not likely to respond to CAR T-cellmonotherapy if the identified tumor type is solid tumor cancer type D.

In some embodiments, a CAR T-cell expresses an antigen binding domainthat targets CD19, CD20, or CD30.

In some embodiments, a subject has a blood cancer.

In some embodiments, a subject has a lymphoma. In some embodiments, thelymphoma is diffuse large B cell lymphoma (DLBCL).

In some embodiments, a subject has leukemia. In some embodiments, asubject has a solid cancer. In some embodiments, the subject hasmelanoma.

In some embodiments, the method further comprises administering a CAR-Ttherapy to the subject when it is determined that the subject is likelyto respond to the CAR-T therapy.

In some embodiments, the method further comprises administering to thesubject one or more therapeutic agents that are not and adoptive celltransfer therapy. In some embodiments, the one or more therapeuticagents comprise a small molecule, peptide, protein, antibody, inhibitorynucleic acid, mRNA, or any combination thereof. In some embodiments, theone or more therapeutic agents comprises a CD137 activator, PI3Kdelta/gamma inhibitor, immune checkpoint inhibitor, EZH2 inhibitor, BCL2inhibitor, immunomodulator, anti-angiogenic agent, TGFBR2 inhibitor, WNTinhibitor, cytokine therapy, BKT inhibitors, personalized cancervaccine, or any combination thereof. In some embodiments, the one ormore therapeutic agents comprises Utomilumab, Lenalidomide, Rituximab,Rituximab+Lenalidomide, Umbralisib, nivolumab, ipilimumab, Tazemetostat,venetoclax, a TLR 1, 2, 7, or 9 agonist, Azacitidine, Ibrutinib,Selinexor, Utomilumab, IL2, IFNa, or any combination thereof.

In some embodiments, a method for determining whether or not a subjectis likely to respond to an adoptive cell transfer therapy furthercomprising producing a report. In some embodiments, producing a reportcomprises (i) a recommendation to administer an adoptive cell transfertherapy to a subject that is likely to respond to the adoptive celltransfer therapy; or (ii) a recommendation to administer a non-adoptivecell transfer therapy to a subject that is unlikely to respond to anadoptive cell transfer therapy.

In some aspects, the disclosure provides a method of treating diffuselarge B cell lymphoma (DLBCL) in a subject in need thereof byadministering to the subject an adoptive cell therapy based upon adetermination that the subject has a type A tumor microenvironment (TME)or type D TME.

In some aspects, the present disclosure provides an adoptive celltherapy for use in treating diffuse large B cell lymphoma (DLBCL) in asubject in need thereof, wherein the subject has been determined using amethod described herein as likely to respond to the adoptive celltherapy.

In some aspects, the present disclosure provides an adoptive celltherapy for use in treating diffuse large B cell lymphoma (DLBCL) in asubject in need thereof, wherein the subject has been determined using amethod described herein as having a type A TME or a type D TME.

In some embodiments, a subject has not previously been treated forDLBCL. In some embodiments, a subject has not previously beenadministered a CD20-targeting agent. In some embodiments, the subjecthas not previously been administered rituximab.

In some embodiments, a subject does not have a DLBCL type selected fromDHIT+/MYC+, EZB, and A53.

In some embodiments, an adoptive cell therapy comprises a CAR T-celltherapy.

In some embodiments, the determination that the subject has a type D TMEhas been made according to a method comprising: using at least onecomputer hardware processor to perform: obtaining sequencing data from abiological sample obtained from the subject; determining amolecular-functional (MF) expression signature for the subject using thesequencing data; and identifying that the subject has a type D TME usingthe determined MF expression signature for the subject.

In some aspects, the disclosure provides a method of treating a solidtumor cancer in a subject in need thereof, the method comprisingadministering to the subject an adoptive cell therapy based upon adetermination that the subject has a type A tumor microenvironment(TME), type B TME, or type D TME.

In some aspects, an adoptive cell therapy for use in treating a solidtumor cancer in a subject in need thereof, wherein the subject has beendetermined using a method described herein as likely to respond to theadoptive cell therapy.

In some aspects, an adoptive cell therapy for use in treating a solidtumor cancer in a subject in need thereof, wherein the subject has beendetermined using a method described herein as having a type A TME, atype B TME, or a type D TME.

In some embodiments, an adoptive cell therapy comprises a CAR T-celltherapy.

In some embodiments, the determination of the subjects TME type has beenmade according to a method comprising: using at least one computerhardware processor to perform: obtaining sequencing data from abiological sample obtained from the subject; determining amolecular-functional (MF) expression signature for the subject using thesequencing data; and identifying that the subject has a type A, TME,type B TME, or type D TME using the determined MF expression signaturefor the subject.

In some embodiments, determining the molecular-functional (MF) signaturecomprises processing the sequencing data to obtain gene expression data.

In some aspects, the disclosure provides a method of treating a solidtumor cancer in a subject in need thereof, the method comprisingadministering to the subject a therapeutic agent other than a CAR T-celltherapy based on a determination that the subject has a solid tumorcancer type C tumor microenvironment (TME).

In some aspects, a therapeutic agent for use in treating a solid tumorcancer in a subject, wherein the subject has been determined using amethod described herein as unlikely to respond to the CAR T-celltherapy.

In some aspects, a therapeutic agent for use in treating a solid tumorcancer in a subject, wherein the subject has been determined using amethod described herein as having a type C TME.

In some embodiments, the determination that the subject has a type C TMEhas been made according to a method comprising: using at least onecomputer hardware processor to perform: obtaining sequencing data from abiological sample obtained from the subject; determining amolecular-functional (MF) expression signature for the subject using thesequencing data; and identifying that the subject has a type C TME usingthe determined MF expression signature for the subject.

In some aspects, the disclosure provides a method of treating a bloodcancer or lymphoma in a subject in need thereof, the method comprisingadministering to the subject a therapeutic agent other than a CAR T-celltherapy based on a determination that the subject has a blood cancertype A tumor microenvironment (TME).

Aspects of the disclosure relate to methods, systems, computer-readablestorage media, and graphical user interfaces (GUIs) that are useful forcharacterizing subjects having certain cancers, for example lymphomas.The disclosure is based, in part, on methods for determining thelymphoma microenvironment (LME) type of a lymphoma (e.g., Diffuse LargeB Cell Lymphoma (DLBCL)) subject. In some embodiments, methods compriseidentifying the subjects prognosis, such as overall survival (OS) and/orprogression-free survival (PFS), based upon the LME type determination.In some embodiments, methods described herein are useful for stratifyingpatient risk or predicting patient survival.

Accordingly, in some aspects, the disclosure provides a method fordetermining a Diffuse Large B cell lymphoma (DLBCL) microenvironment(LME) type of a subject, the method comprising using at least onecomputer hardware processor to perform:

obtaining sequencing data for a subject having, suspected of having, orat risk of having a DLBCL; determining a LME signature for the subjectusing the sequencing data, wherein the LME signature is obtained using:(i) a gene expression signature comprising a plurality of gene groupexpression scores for a respective plurality of gene groups; and/or (ii)one or more PROGENY pathway scores for the sequencing data; andassigning, from a plurality of LME types, an LME type to the subjectusing the LME signature.

In some aspects, the disclosure provides a method for providing aprognosis, predicting survival or stratifying patient risk of a subjectsuspected of having, or at risk of having a Diffuse Large B celllymphoma (DLBCL), the method comprising determining a DLBCLmicroenvironment (LME) type of the subject as described herein.

In some embodiments, the plurality of gene groups includes at leastthree gene groups listed in Table 3, and wherein obtaining the LMEsignature for the subject comprises determining at least three genegroups listed in Table 3 using one or more genes listed in Table 3 foreach of the respective groups.

In some embodiments, obtaining the LME signature for the subjectcomprises using the sequencing data to determine gene group expressionscores for one or more gene groups listed in Table 3, each of whichincludes determining one or more gene groups listed in Table 3 using oneor more genes listed in Table 3 for each of the respective groups.

In some embodiments, the one or more PROGENY pathway scores comprisesNFkB, PI3K, and/or p53 signaling signatures.

In some embodiments, the plurality of LME types includes LME-A type,LME-B type, LME-C type, and LME-D type.

In some embodiments, the plurality of gene groups includes at leastthree of the following gene groups, and wherein obtaining the LMEsignature for the subject comprises: In some embodiments, determiningthe molecular-functional (MF) expression signature comprises using thesequencing data to determine gene group expression scores for at leastone (e.g., 1, 2, 3, 4, 5, or more) of the following gene groups:Lymphatic endothelium (LEC), Angiogenesis (VEC), Cancer-associatedfibroblasts (CAF), Fibroblastic reticular cells (FRC), Matrix (ECM),Matrix Remodeling (ECM remodeling), Granulocyte traffic, Protumorcytokines (IS cytokines), Follicular Dendritic Cells (FDC), Macrophages,M1 signature (activated M1), Effector cell traffic (T cell traffic),Major histocompatibility complex II (MHC-II), Major histocompatibilitycomplex I (MHC-I), Follicular B helper T cells (TFH), Regulatory T cells(Treg), T cells (TIL), Checkpoint inhibition (IS checkpoints), NaturalKiller Cells (NK cells), B cell traffic, Benign B cells (B cells), Tumorproliferation rate (cell proliferation), Nuclear factor kappa B (NFkB),Phosphoinositide 3-kinase (PI3K), and p53.

In some embodiments, determining the lymphoma microenvironment (LME)signature comprises using the sequencing data to determine gene groupexpression scores for one or more genes (e.g., 1, 2, 3, 4, 5, or more)of the following gene groups using gene expression data from one or moregenes (e.g., 1, 2, 3, 4, 5, or more) of the respective following sets ofgenes: Lymphatic endothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN, CXADR,FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, and JAM2; Angiogenesis(VEC): CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2, ANGPT1, CXCL5,FLT1, VEGFA, KDR, VEGFB, and ANGPT2; Cancer-associated fibroblasts(CAF): COL1A1, WP2, LGALS1, WP7, LRP1, CD248, S100A4, FAP, FGF2, WP9,CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1, WP3, CA9, PRELP, FBLN1,COL6A3, COL11A1, TGFB3, WP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1,LUM, LGALS9, PTGS2, and TGFB2; Fibroblastic reticular cells (FRC):PDGFRA, ACTA2, ICAM1, NT5E, VIM, PDPN, THY1, DES, VCAM1, PTGS2, andLTBR; Matrix (ECM): COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, andCOL4A1; Matrix Remodeling (ECM remodeling): TIMP1, TIMP2, MMP2, MMP9,and CA9; Granulocyte traffic: KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT,CCL11, CCR3, CXCL1, and CXCL2; Protumor cytokines (IS cytokines): CCL4,IL6, TNFSF13B, MIF, CXCL8, IL22, and IL10; Follicular Dendritic Cells(FDC): PDPN, TNFRSF1A, LTBR, FDCSP, CLU, PRNP, and BST1; Macrophages:IL10, MSR1, ARG1, CSF1R, CD163, MRC1, and CSF1; M1 signature (activatedM1): TNF, NOS2, IL1B, and CMKLR1; Effector cell traffic (T celltraffic): CXCL11, CXCL10, CXCL9, CXCR3, CX3CL1, CCL5, and CX3CR1; Majorhistocompatibility complex II (MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1,HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, and HLA-DMB; Majorhistocompatibility complex I (MHC-I): TAP1, HLA-C, B2M, HLA-B, HLA-A,and TAP2; Follicular B helper T cells (TFH): CD40LG, SH2D1A, CD84,CXCR5, IL4, IL6, MAF, BCL6, IL21, and ICOS; Regulatory T cells (Treg):CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, and TNFRSF18; T cells (TIL):CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC, and CD3G;Checkpoint inhibition (IS checkpoints): CTLA4, HAVCR2, CD274, PDCD1,BTLA, TIGIT, PDCD1LG2, and LAG3; Natural Killer Cells (NK cells):SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG, GNLY, NCR1, CD226,NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1; B cell traffic: CXCL13,CXCR5, CCR6, and CCL20; Benign B cells (B cells): CD79B, MS4A1, STAP1,TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5, CD79A, TNFRSF13C, andFCRL5; and Tumor proliferation rate (cell proliferation): MCM6, AURKB,ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3,CDK2, PLK1, and BUB1.

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Lymphaticendothelium (LEC).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofAngiogenesis (VEC).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofCancer-associated fibroblasts (CAF).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofFibroblastic reticular cells (FRC).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Matrix(ECM).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of MatrixRemodeling (ECM remodeling).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of FollicularDendritic Cells (FDC).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set ofMacrophages.

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of M1signature (activated M1).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Majorhistocompatibility complex I (MHC-I).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Majorhistocompatibility complex II. (MHC-II).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of FollicularB helper T cells (TFH).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of RegulatoryT cells (Treg).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of T cells(TIL).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Benign Bcells (B cells).

In some embodiments, the gene group expression score for one or moregenes (e.g., 1, 2, 3, 4, 5, or more) is from the gene set of Tumorproliferation rate (cell proliferation).

In some embodiments, determining the LME signature further comprisesdetermining the PROGENY pathway scores for one or more of Nuclear factorkappa B (NFkB), Phosphoinositide 3-kinase (PI3K), and p53. In someembodiments, determining the molecular-functional (MF) expressionsignature further comprises determining the PROGENY pathway scores foreach of Nuclear factor kappa B (NFkB), Phosphoinositide 3-kinase (PI3K),and p53.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theLymphatic endothelium (LEC) gene group using one or more (e.g., 1, 2, 3,4, 5, or more) genes selected from: JAM3, PPP1R13B, CXCL12, PDPN, CXADR,FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, and JAM2.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theAngiogenesis (VEC) gene group using one or more (e.g., 1, 2, 3, 4, 5, ormore) genes selected from: CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF,CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, and ANGPT2.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theCancer-associated fibroblasts (CAF) gene group using one or more (e.g.,1, 2, 3, 4, 5, or more) Cancer-associated fibroblasts genes selectedfrom: COL1A1, WP2, LGALS1, WP7, LRP1, CD248, S100A4, FAP, FGF2, WP9,CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1, WP3, CA9, PRELP, FBLN1,COL6A3, COL11A1, TGFB3, MMP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1,TGFB1, LUM, LGALS9, PTGS2, and TGFB2.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theFibroblastic reticular cells (FRC) gene group using one or more (e.g.,1, 2, 3, 4, 5, or more) genes selected from: PDGFRA, ACTA2, ICAM1, NT5E,VIM, PDPN, THY1, DES, VCAM1, PTGS2, and LTBR.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theMatrix (ECM) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, andCOL4A1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theMatrix Remodeling (ECM remodeling) gene group using one or more (e.g.,1, 2, 3, 4, 5, or more) genes selected from: TIMP1, TIMP2, WP2, WP9, andCA9.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theGranulocyte traffic gene group using one or more (e.g., 1, 2, 3, 4, 5,or more) genes selected from: KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT,CCL11, CCR3, CXCL1, and CXCL2.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theProtumor cytokines (IS cytokines) gene group using one or more (e.g., 1,2, 3, 4, 5, or more) genes selected from: CCL4, IL6, TNFSF13B, MIF,CXCL8, IL22, and IL10.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theFollicular Dendritic Cells (FDC) gene group using one or more (e.g., 1,2, 3, 4, 5, or more) genes selected from: PDPN, TNFRSF1A, LTBR, FDCSP,CLU, PRNP, and BST1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theMacrophages gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: IL10, MSR1, ARG1, CSF1R, CD163, MRC1, and CSF1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the M1signature (activated M1) gene group using one or more (e.g., 1, 2, 3, 4,or more) genes selected from: TNF, NOS2, IL1B, and CMKLR1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theEffector cell traffic (T cell traffic) gene group using one or more(e.g., 1, 2, 3, 4, 5, or more) genes selected from: CXCL11, CXCL10,CXCL9, CXCR3, CX3CL1, CCL5, and CX3CR1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the Majorhistocompatibility complex II (MHC-II) gene group using one or more(e.g., 1, 2, 3, 4, 5, or more) genes selected from: HLA-DQB1, HLA-DPB1,HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, and HLA-DMB.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the Majorhistocompatibility complex I (MHC-I) gene group using one or more (e.g.,1, 2, 3, 4, 5, or more) genes selected from: TAP1, HLA-C, B2M, HLA-B,HLA-A, and TAP2.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theFollicular B helper T cells (TFH) gene group using one or more (e.g., 1,2, 3, 4, 5, or more) genes selected from: CD40LG, SH2D1A, CD84, CXCR5,IL4, IL6, MAF, BCL6, IL21, and ICOS.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theRegulatory T cells (Treg) gene group using one or more (e.g., 1, 2, 3,4, 5, or more) genes selected from: CCR8, CTLA4, IKZF2, IKZF4, FOXP3,IL10, and TNFRSF18.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the Tcells (TIL) gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E, TRBC1,TRAC, and CD3G.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theCheckpoint inhibition (IS checkpoints) gene group using one or more(e.g., 1, 2, 3, 4, 5, or more) genes selected from: CTLA4, HAVCR2,CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, and LAG3.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theNatural Killer Cells (NK cells) gene group using one or more (e.g., 1,2, 3, 4, 5, or more) genes selected from: SH2D1B, GZMH, GZMB, CD160,KLRK1, NCR3, CD244, IFNG, GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2,KIR2DL4, and KLRF1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the Bcell traffic gene group using one or more (e.g., 1, 2, 3, 4, 5, or more)genes selected from: CXCL13, CXCR5, CCR6, and CCL20.

In some embodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for theBenign B cells (B cells) gene group using one or more (e.g., 1, 2, 3, 4,5, or more) genes selected from: CD79B, MS4A1, STAP1, TNFRSF17, CD24,CD22, TNFRSF13B, BLK, CD19, PAX5, CD79A, TNFRSF13C, and FCRL5. In someembodiments, determining the LME signature comprises using thesequencing data to determine a gene group expression score for the Tumorproliferation rate (cell proliferation) gene group using one or more(e.g., 1, 2, 3, 4, 5, or more) genes selected from: MCM6, AURKB, ESCO2,CCNB1, AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1,and BUB1.

In some embodiments, determining the LME signature comprises using thesequencing data to determine gene group expression scores for each ofthe genes of each of the following gene groups using gene expressiondata from each gene of the respective following sets of genes: Lymphaticendothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21,FOXC2, EDNRB, LYVE1, PROX1, SOX18, and JAM2; Angiogenesis (VEC): CDH5,PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA,KDR, VEGFB, and ANGPT2; Cancer-associated fibroblasts (CAF): COL1A1,WP2, LGALS1, WP7, LRP1, CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1,COL1A2, COL5A1, COL6A1, WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3,MMP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2,and TGFB2; Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1,NT5E, VIM, PDPN, THY1, DES, VCAM1, PTGS2, and LTBR; Matrix (ECM):COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, and COL4A1; Matrix Remodeling(ECM remodeling): TIMP1, TIMP2, WP2, WP9, and CA9; Granulocyte traffic:KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2;Protumor cytokines (IS cytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8,IL22, and IL10; Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A, LTBR,FDCSP, CLU, PRNP, and BST1; Macrophages: IL10, MSR1, ARG1, CSF1R, CD163,MRC1, and CSF1; M1 signature (activated M1): TNF, NOS2, IL1B, andCMKLR1; Effector cell traffic (T cell traffic): CXCL11, CXCL10, CXCL9,CXCR3, CX3CL1, CCL5, and CX3CR1; Major histocompatibility complex II(MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA,HLA-DRB1, and HLA-DMB; Major histocompatibility complex I (MHC-I): TAP1,HLA-C, B2M, HLA-B, HLA-A, and TAP2; Follicular B helper T cells (TFH):CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, and ICOS;Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, andTNFRSF18; T cells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E,TRBC1, TRAC, and CD3G; Checkpoint inhibition (IS checkpoints): CTLA4,HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, and LAG3; Natural KillerCells (NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG,GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1; Bcell traffic: CXCL13, CXCR5, CCR6, and CCL20; Benign B cells (B cells):CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, and FCRL5; and Tumor proliferation rate (cellproliferation): MCM6, AURKB, ESCO2, CCNB1, AURKA, MK167, CCND1, CCNE1,MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, and BUB1. In some embodiments,determining gene group expression scores for each of the genes comprisesdetermining the gene expression data that is available. For example, theavailable gene expression data may include all genes in the gene sets asdisclosed herein. In some embodiments, the available gene expressiondata may not include all genes in the gene sets as disclosed herein.

In some embodiments, the method further comprises administering to thesubject one or more therapeutic agents that are not an adoptive celltransfer therapy. In some embodiments, the subject has a type C TME. Insome embodiments, the one or more therapeutic agents comprise a smallmolecule, peptide, protein, antibody, inhibitory nucleic acid, mRNA, orany combination thereof. In some embodiments, the one or moretherapeutic agents comprises a CD137 activator, PI3K delta/gammainhibitor, immune checkpoint inhibitor, EZH2 inhibitor, BCL2 inhibitor,immunomodulator, anti-angiogenic agent, TGFBR2 inhibitor, WNT inhibitor,BKT inhibitors, cytokine therapy, personalized cancer vaccine, or anycombination thereof. In some embodiments, the one or more therapeuticagents comprises Utomilumab, Lenalidomide, Rituximab,Rituximab+Lenalidomide, Umbralisib, nivolumab, ipilimumab, Tazemetostat,venetoclax, a TLR 1, 2, 7, or 9 agonist, Azacitidine, Ibrutinib,Selinexor, Utomilumab, IL2, IFNa, or any combination thereof.

In some aspects, the disclosure provides a method for treating a subjecthaving Diffuse Large B cell lymphoma (DLBCL), the method comprisingadministering to a subject having been identified as having DLBCLcharacterized by a type LME-C or type LME-A one or moreimmunotherapeutic agents.

In some embodiments, the DLBCL is Activated B cell (ABC) DLBCL. In someembodiments, the DLBCL is Germinal center B cell-like (GCB) DLBCL.

In some embodiments, methods described herein further compriseidentifying the subject as having a deceased chance of a PFS24 event(e.g., relapse, retreatment, or death) relative to other LME types whenthe subject is assigned type LME-C or LME-A.

In some embodiments, methods described herein further compriseidentifying the subject as having an increased chance of a PFS24 event(e.g., relapse, retreatment, or death) relative to other LME types whenthe subject is assigned type LME-D.

In some embodiments, methods described herein further comprise obtainingan International Prognostic Index (IPI) score of the subject. In someembodiments, the IPI score is

Low, Intermediate, or High.

In some embodiments, methods described herein comprise identifying thesubject as having a deceased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the DLBCL istype LME-C ABC and the IPI score is High.

In some embodiments, methods described herein comprise identifying thesubject as having an increased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the DLBCL istype LME-D GCB and the IPI score is High.

In some embodiments, methods described herein comprise identifying thesubject as having an increased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the DLBCL istype LME-A or LME-D ABC and the IPI score is Intermediate.

In some embodiments, the subject is a mammal. In some embodiments, thesubject is a human.

In some embodiments, methods described herein further comprise providinga recommendation to administer one or more immunotherapeutic agents tothe subject. In some embodiments, the immunotherapeutic agent comprisesRituximab.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1A provides an example of a processes for identifying the tumormicroenvironment (TME) type of a subject, according to some aspects ofthe invention. In some embodiments, the process includes obtainingsequencing data from a biological sample obtained from a subject,processing the sequencing data to obtain gene expression data,processing the gene expression data to obtain gene enrichment scores forgene groups, producing a molecular-functional expression signature(MFES), identifying a TME type based on the MFES, and determiningwhether or not a subject is likely to respond to an adoptive celltransfer therapy based on the TME type. In some embodiments, the methodcomprises normalizing the MFES to the MFES of a cohort of samples withsimilar cancer diagnosis (e.g., solid tumor), the protocol of which aredescribed in U.S. Pat. No. 10,311,967, the entire contents of which areincorporated herein by reference. In some embodiments, the methodfurther comprises administering an identified therapy (e.g., an adoptivecell transfer therapy, such as CAR-T therapy) to the subject.

FIG. 1 B provides an example of a processes for identifying the lymphomamicroenvironment (LME) type of a subject, according to some aspects ofthe invention. In some embodiments, the process includes obtainingsequencing data from a biological sample obtained from a subject,processing the sequencing data to obtain gene expression data,processing the gene expression data to obtain gene enrichment scores forgene groups and PROGENY pathway scores, producing a lymphomamicroenvironment (LME) signature, and identifying a LME type based onthe LME signature. In some embodiments, the method further comprisesproviding a recommendation to administer one or more immunotherapeuticagents based on the LME type.

FIG. 2 shows representative gene expression data for identification offour tumor microenvironment types (A, B, C, and D), based upon molecularfunction profiling of cancer cells from 4244 lymphoma subjects across 20datasets. Data shown in red represents “high.” Data shown in bluerepresents “low.” The scale of the signatures was [−2, 2].

FIG. 3 shows representative data indicating that LymphomaMicroenvironment (LME) types correlate with overall survival (OS),independent of cancer cell of origin (COO), according to certain aspectsof the invention. Left panel shows a Kaplan-Meier (KM) survival plot fora sample of 1010 patients having Activated B cell (ABC) lymphoma. Rightpanel shows a KM survival plot for a sample of 1456 patients havingGerminal center B cell-like (GCB) lymphoma.

FIG. 4 shows representative data indicating that LymphomaMicroenvironment (LME) types correlate with progression-free survival(PFS), independent of cancer cell of origin (COO), according to certainaspects of the invention. Left panel shows a Kaplan-Meier (KM) survivalplot for a cohort of 839 patients having Activated B cell (ABC)lymphoma. Right panel shows a KM survival plot for a cohort of 1194patients having Germinal center B cell-like (GCB) lymphoma.

FIG. 5 shows representative data demonstrating stratification ofprogression-free survival at 24 months (PFS24) according to COO and LMEtype, according to certain aspects of the invention. The left panelshows stratification of subjects having Activated B cell (ABC) DCBCL andthe right panel shows stratification of subjects having Germinal centerB cell-like (GCB) DCBCL.

FIG. 6 shows representative data demonstrating stratification ofprogression-free survival at 24 months (PFS24) according to COO, LMEtype, and International Prognostic Index (IPI), according to certainaspects of the invention. Data indicate poor prognosis for groups “ABCIPI-High” and (not LME-C, e.g., LME-A, LME-B, or LME-D) or “GCBIPI-High” LME4; ABC IPI-Intermediate LME3/4 subjects also havenon-favorable PFS24. As disclosed herein, “ABC IPI-High,” “ABCIPI-Intermediate,” and “ABC-Low” can be used interchangeably with “ABCHigh,” “ABC Intermediate,” and “ABC Low.” As disclosed herein, “GCBIPI-High,” “GCB IPI-Intermediate,” and “GCB-Low” can be usedinterchangeably with “GCB High,” “GCB Intermediate,” and “GCB Low.”

DETAILED DESCRIPTION

Aspects of the disclosure relate to compositions and methods fordetermining whether or not a subject is likely to respond to certainadoptive cell therapies (e.g., chimeric antigen receptor (CAR) T-celltherapy, etc.). In some embodiments, the methods comprise the steps ofidentifying a subject as having a tumor microenvironment (TME) typebased upon a molecular-functional (MF) expression signature of thesubject, and determining whether or not the subject is likely to respondto a chimeric antigen receptor (CAR) T-cell therapy based upon the TMEtype. In some embodiments, “determining whether or not a subject islikely to respond” to a CAR-T cell therapy comprises identifying thesubject as a candidate for CAR-T therapy, or assisting in theidentification of a subject as a candidate for CAR-T therapy.

Also described herein is a computer system comprising at least oneprocessor; and at least one non-transitory computer readable mediumcontaining instructions that, when executed by the at least oneprocessor, cause the at least one processor to perform the method of anyembodiment of any aspect described herein.

Also described herein is a non-transitory computer readable mediumcomprising instructions that, when executed by at least one processor,cause the at least one processor to perform the method of any embodimentof any aspect described herein.

In some embodiments, the methods comprise administering one or moretherapeutic agents (e.g., CAR T-cell therapy, chemotherapy,radiotherapy, immunotherapy, and combinations thereof) to the subjectbased on the determining of TME type.

Cancer

Aspects of the disclosure relate to methods of determining the TME typeof a subject having, suspected of having, or at risk of having cancer. Asubject may be any mammal, for example a human, non-human primate,rodent (e.g., rat, mouse, guinea pig, etc.), dog, cat, horse etc. Insome embodiments, a subject is a human.

As used herein, “cancer” refers to a disease or diseases caused by anuncontrolled division of abnormal cells in a part (or parts) of thebody. Examples of cancers include but are not limited to bladder cancer,breast cancer, colon and rectal cancer, endometrial cancer, kidneycancer, leukemias, liver cancer, lung cancer, melanoma, lymphomas,pancreatic cancer, prostate cancer, thyroid Cancer, bone cancer, etc. Insome embodiments, a cancer is classified as a solid tumor cancer or ablood cancer (e.g., hematological cancer). Examples of solid tumorcancers include but are not limited to sarcomas and carcinomas,glioblastomas, and melanomas. Examples of blood cancers includeleukemias, such as Acute myeloid (or myelogenous) leukemia (AML),Chronic myeloid (or myelogenous) leukemia (CML), Acute lymphocytic (orlymphoblastic) leukemia (ALL), and Chronic lymphocytic leukemia (CLL),and lymphomas (which may also form solid tumors). In some embodiments, alymphoma is a diffuse large B-cell lymphoma (DLBCL), Activated B-celldiffuse large B-cell lymphoma (ABC), or Germinal center B-cell likediffuse large B-cell lymphoma (GCB).

In some embodiments, a biological sample comprises tumor cells (e.g.,cancerous tumor cells). In some embodiments, a biological samplecomprises tumor cells and non-cancerous cells, for example non-canceroustumor cells and/or cells present in the tumor microenvironment. Such asample, in some embodiments, is referred to as a ‘mixed sample’. A mixedsample of cells from a tumor can be cancer cells and non-cancerous cellsincluding but are not limited to fibroblasts, immune cells and cellsthat comprise the blood vessels, proteins produced by the tumor, tumorstroma, and associated tissue cells.

In some embodiments, a subject having cancer exhibits one or more signsor symptoms of the cancer, for example, the presence of tumors, etc. Insome embodiments, a subject suspected of having cancer exhibits one ormore signs or symptoms of cancer, or is characterized by the presence ofone or more features that predisposes the subject to cancer, for examplethe presence of pre-cancerous tumor cells, genetic mutations in tumorsuppressor genes, etc.

In some embodiments, a biological sample is obtained from a subject forthe purpose of determining a TME type. A biological sample may be fromany source in the subjects body including, but not limited to, any fluid[such as blood (e.g., whole blood, blood serum, or blood plasma),saliva, tears, synovial fluid, cerebrospinal fluid, pleural fluid,pericardial fluid, ascitic fluid, and/or urine], hair, skin (includingportions of the epidermis, dermis, and/or hypodermis), oropharynx,laryngopharynx, esophagus, stomach, bronchus, salivary gland, tongue,oral cavity, nasal cavity, vaginal cavity, anal cavity, bone, bonemarrow, brain, thymus, spleen, small intestine, appendix, colon, rectum,anus, liver, biliary tract, pancreas, kidney, ureter, bladder, urethra,uterus, vagina, vulva, ovary, cervix, scrotum, penis, prostate,testicle, seminal vesicles, and/or any type of tissue (e.g., muscletissue, epithelial tissue, connective tissue, or nervous tissue). Thebiological sample may be any type of sample including, for example, asample of a bodily fluid, one or more cells, a piece of tissue, or someor all of an organ. In some embodiments, the sample may be from acancerous tissue or organ or a tissue or organ suspected of having oneor more cancerous cells. Accordingly, in some embodiments a sample is acancer or tumor biopsy.

Biological Samples

Aspects of the disclosure relate to methods for determining whether ornot a subject is likely to respond to an adoptive cell transfer therapyor determining a Diffuse Large B cell lymphoma (DLBCL) microenvironment(LME) type of a subject by obtaining sequencing data from a biologicalsample that has been obtained from the subject.

The biological sample may be from any source in the subjects bodyincluding, but not limited to, any fluid [such as blood (e.g., wholeblood, blood serum, or blood plasma), saliva, tears, synovial fluid,cerebrospinal fluid, pleural fluid, pericardial fluid, ascitic fluid,and/or urine], hair, skin (including portions of the epidermis, dermis,and/or hypodermis), oropharynx, laryngopharynx, esophagus, stomach,bronchus, salivary gland, tongue, oral cavity, nasal cavity, vaginalcavity, anal cavity, bone, bone marrow, brain, thymus, spleen, smallintestine, appendix, colon, rectum, anus, liver, biliary tract,pancreas, kidney, ureter, bladder, urethra, uterus, vagina, vulva,ovary, cervix, scrotum, penis, prostate, testicle, seminal vesicles,and/or any type of tissue (e.g., muscle tissue, epithelial tissue,connective tissue, or nervous tissue). In some embodiments, the tissuesample comprises a gastrointestinal tissue sample. Examples ofgastrointestinal tissue samples include but are not limited to mucosaltissue, submucosal tissue, muscular layer tissue, and serous layertissue (also referred to as serosa tissue). In some embodiments, agastrointestinal tissue sample comprises one or more cell types derivedfrom a stomach (e.g., mucous cells, parietal cells, chief cells,endocrine cells, etc.). In some embodiments, a gastrointestinal tissuesample comprises one or more cell types derived from gastrointestinaltissue, for example enterocytes, Paneth cells, goblet cells,neuroendocrine cells, etc.

The biological sample may be any type of sample including, for example,a sample of a bodily fluid, one or more cells, a piece of tissue, orsome or all of an organ. In some embodiments, the sample may be from acancerous tissue or organ or a tissue or organ suspected of having oneor more cancerous cells. In some embodiments, the sample may be from ahealthy (e.g., non-cancerous) tissue or organ. In some embodiments, thesample from a healthy (e.g., non-cancerous) tissue or organ may be fromsubjects who are at risk or suspected of having the risk of developingcancer. In some embodiments, the sample from a healthy (e.g.,non-cancerous) tissue or organ may be from tissues surrounding one ormore cancerous cells. In some embodiments, a sample from a subject(e.g., a biopsy from a subject) may include both healthy and cancerouscells and/or tissue. In certain embodiments, one sample will be takenfrom a subject for analysis. In some embodiments, more than one (e.g.,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ormore) samples may be taken from a subject for analysis. In someembodiments, one sample from a subject will be analyzed. In certainembodiments, more than one (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, 15, 16, 17, 18, 19, 20, or more) samples may be analyzed. Ifmore than one sample from a subject is analyzed, the samples may beprocured at the same time (e.g., more than one sample may be taken inthe same procedure), or the samples may be taken at different times(e.g., during a different procedure including a procedure 1, 2, 3, 4, 5,6, 7, 8, 9, 10 days; 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 weeks; 1, 2, 3, 4, 5,6, 7, 8, 9, 10 months, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 years, or 1, 2, 3,4, 5, 6, 7, 8, 9, 10 decades after a first procedure). A second orsubsequent sample may be taken or obtained from the same region (e.g.,from the same tumor or area of tissue) or a different region (including,e.g., a different tumor). A second or subsequent sample may be taken orobtained from the subject after one or more treatments, and may be takenfrom the same region or a different region. A second or subsequentsample may be taken or obtained from the subject when the first samplefrom the subject was taken. For example, two separate samples can betaken during the same procurement. These two separate samples can bepooled or compared for the analysis as disclosed herein. As anon-limiting example, the second or subsequent sample may be useful indetermining whether the cancer in each sample has differentcharacteristics (e.g., in the case of samples taken from two physicallyseparate tumors in a patient) or whether the cancer has responded to oneor more treatments (e.g., in the case of two or more samples from thesame tumor prior to and subsequent to a treatment).

Any of the biological samples described herein may be obtained from thesubject using any known technique. In some embodiments, the biologicalsample may be obtained from a surgical procedure (e.g., laparoscopicsurgery, microscopically controlled surgery, or endoscopy), bone marrowbiopsy, punch biopsy, endoscopic biopsy, or needle biopsy (e.g., afine-needle aspiration, core needle biopsy, vacuum-assisted biopsy, orimage-guided biopsy). In some embodiments, each of the at least onebiological sample is a bodily fluid sample, a cell sample, or a tissuebiopsy.

Sequencing Data and Gene Expression Data

Expression data (e.g., RNA expression data and/or whole exome sequencing(WES) data) as described herein may be obtained from a variety ofsources. In some embodiments, expression data may be obtained byanalyzing a biological sample from a patient. In some embodiments, abiological sample is processed using a sequencing platform (e.g., DNAsequencing platform, RNA sequencing platform, exome sequencing platform,microarray sequencing platform, etc.) to produce sequencing data. Insome embodiments, the sequencing data is processed to produce expressiondata. In some embodiments, RNA sequence data is processed by one or morebioinformatics methods or tools, for example RNA sequence quantificationtools (e.g., Kallisto) and genome annotation tools (e.g., Gencode v23),in order to produce expression data. In some embodiments, microarrayexpression data is processed using a bioinformatics R package, such as“affy” or “limma”, in order to produce expression data. In someembodiments, sequencing data and/or expression data comprises more than5 kilobases (kb). In some embodiments, the size of the obtained RNAand/or DNA sequence data is at least 10 kb. In some embodiments, thesize of the obtained RNA and/or DNA sequence data is at least 100 kb. Insome embodiments, the size of the obtained RNA and/or DNA sequence datais at least 500 kb. In some embodiments, the size of the obtained RNAand/or DNA sequence data is at least 1 megabase (Mb). In someembodiments, the size of the obtained RNA and/or DNA sequence data is atleast 10 Mb. In some embodiments, the size of the obtained RNA and/orDNA sequence data is at least 100 Mb. In some embodiments, the size ofthe obtained RNA and/or DNA sequence data is at least 500 Mb. In someembodiments, the size of the obtained RNA and/or DNA sequence data is atleast 1 gigabase (Gb). In some embodiments, the size of the obtained RNAand/or DNA sequence data is at least 10 Gb. In some embodiments, thesize of the obtained RNA and/or DNA sequence data is at least 100 Gb. Insome embodiments, the size of the obtained RNA and/or DNA sequence datais at least 500 Gb.

Expression Data

Expression data (e.g., indicating expression levels) for a plurality ofgenes may be used for any of the methods described herein. The number ofgenes which may be examined may be up to and inclusive of all the genesof the subject. In some embodiments, expression levels may be examinedfor all of the genes of a subject. In some embodiments, the number ofgenes which may be examined may be more than all the genes of thesubject. As a non-limiting example, four or more, five or more, six ormore, seven or more, eight or more, nine or more, ten or more, eleven ormore, twelve or more, 13 or more, 14 or more, 15 or more, 16 or more, 17or more, 18 or more, 19 or more, 20 or more, 21 or more, 22 or more, 23or more, 24 or more, 25 or more, 26 or more, 27 or more, 28 or more, 29or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80or more, 90 or more, 100 or more, 125 or more, 150 or more, 175 or more,200 or more, 225 or more, 250 or more, 275 or more, or 300 or more genesmay be used for any evaluation described herein. As another set ofnon-limiting examples, at least four, at least five, at least six, atleast seven, at least eight, at least nine, at least ten, at leasteleven, at least twelve, at least 13, at least 14, at least 15, at least16, at least 17, at least 18, at least 19, at least 20, at least 21, atleast 22, at least 23, at least 24, at least 25, at least 26, at least27, at least 28, at least 29, at least 30, at least 40, at least 50, atleast 60, at least 70, at least 80, at least 90, at least 100, at least125, at least 150, at least 175, at least 200, at least 225, at least250, at least 275, or at least 300 genes may be used for any evaluationdescribed herein. In some embodiments, at least two, at least three, atleast four, at least five, at least six, at least seven, at least eight,at least nine, at least ten, at least eleven, at least twelve, at least13, at least 14, at least 15, at least 16, at least 17, at least 18, atleast 19, at least 20, at least 21, at least 22, at least 23, at least24, at least 25, at least 26, at least 27, at least 28, at least 29, atleast 30, at least 40, at least 50, at least 60, at least 70, at least80, at least 90, at least 100, at least 125, at least 150, at least 175,at least 200, at least 225, at least 250, at least 275, or at least 300genes may be examined for each gene group evaluation described herein.In some embodiments, up to 50 genes (e.g., up to two, up to three, up tofour, up to five, up to six, up to seven, up to eight, up to nine, up toten, up to eleven, up to twelve, up to 13, up to 14, up to 15, up to 16,up to 17, up to 18, up to 19, up to 20, up to 21, up to 22, up to 23, upto 24, up to 25, up to 26, up to 27, up to 28, up to 29, up to 30, up to31, up to 32, up to 33, up to 34, up to 35, up to 36, up to 37, up to38, up to 39, up to 40, up to 41, up to 42, up to 43, up to 44, up to45, up to 46, up to 47, up to 48, up to 49, or up to 50) gene groups maybe used for any evaluation described herein.

Any method may be used on a sample from a subject in order to acquireexpression data (e.g., indicating expression levels) for the pluralityof genes. As a set of non-limiting examples, the expression data may beRNA expression data, DNA expression data, or protein expression data.

DNA expression data, in some embodiments, refers to a level of DNA in asample from a subject. The level of DNA in a sample from a subjecthaving cancer may be elevated compared to the level of DNA in a samplefrom a subject not having cancer, e.g., due to a gene duplication in acancer patients sample. The level of DNA in a sample from a subjecthaving cancer may be reduced compared to the level of DNA in a samplefrom a subject not having cancer, e.g., a gene deletion in a cancerpatients sample.

RNA expression data, in some embodiments, refers to data for DNA (orgene) expressed in a sample, for example, sequencing data for a genethat is expressed in a patients sample. In some embodiments, RNAexpression data comprises RNA sequencing (RNAseq) data. Such data may beuseful, in some embodiments, to determine whether the patient has one ormore mutations associated with a particular cancer.

RNA expression data may be acquired using any method known in the artincluding, but not limited to: whole transcriptome sequencing, total RNAsequencing, mRNA sequencing, targeted RNA sequencing, small RNAsequencing, ribosome profiling, RNA exome capture sequencing, and/ordeep RNA sequencing. DNA expression data may be acquired using anymethod known in the art including any known method of DNA sequencing.For example, DNA sequencing may be used to identify one or moremutations in the DNA of a subject. Without wishing to be bound by anytheory, genome sequencing can be used for the purpose of DNA sequencingas disclosed herein. Any technique used in the art to sequence DNA maybe used with the methods described herein. As a set of non-limitingexamples, the DNA may be sequenced through single-molecule real-timesequencing, ion torrent sequencing, pyrosequencing, sequencing bysynthesis, sequencing by ligation (SOLiD sequencing), nanoporesequencing, or Sanger sequencing (chain termination sequencing). Proteinexpression data may be acquired using any method known in the artincluding, but not limited to: N-terminal amino acid analysis,C-terminal amino acid analysis, Edman degradation (including though useof a machine such as a protein sequenator), or mass spectrometry.

In some embodiments, the expression data comprises whole exomesequencing (WES) data. In some embodiments, the expression datacomprises whole genome sequencing (WGS) data. In some embodiments, theexpression data comprises next-generation sequencing (NGS) data. In someembodiments, the expression data comprises microarray data.

In some embodiments, expression data is used to determine gene groupexpression levels. In some embodiments, gene group expression levels canbe calculated to obtain gene expression scores. In some embodiments,gene group expression levels can be calculated to obtain gene enrichmentscores. For example, in some embodiments, the gene group expressionlevels are calculated as a single sample gene set enrichment analysis(ssGSEA) score for the gene group for each sample independently. In someembodiments, each gene is weighted equally. Methods of performing GSEAare known in the art, for example as described by Reimand et al., NatureProtocols volume 14, pages 482-517 (2019) and Subramanian et al., ProcNatl Acad Sci USA 2005; 102(43):15545-50. In some embodiments, the GSEAis single sample Gene Set Enrichment Analysis (ssGSEA), which is furtherdescribed herein in the section entitled “Molecular Functional (MF)Expression Signatures”.

Assays

Any of the biological samples described herein can be used for obtainingexpression data using conventional assays or those described herein.Expression data, in some embodiments, includes gene expression levels.Gene expression levels may be detected by detecting a product of geneexpression such as mRNA and/or protein.

In some embodiments, gene expression levels are determined by detectinga level of a mRNA in a sample. As used herein, the terms “determining”or “detecting” may include assessing the presence, absence, quantityand/or amount (which can be an effective amount) of a substance within asample, including the derivation of qualitative or quantitativeconcentration levels of such substances, or otherwise evaluating thevalues and/or categorization of such substances in a sample from asubject.

The level of nucleic acids encoding a gene in a sample can be measuredvia a conventional method. In some embodiments, measuring the expressionlevel of nucleic acid encoding the gene comprises measuring mRNA. Insome embodiments, the expression level of mRNA encoding a gene can bemeasured using real-time reverse transcriptase (RT) Q-PCR or a nucleicacid microarray. Methods to detect nucleic acid sequences include, butare not limited to, polymerase chain reaction (PCR), reversetranscriptase-PCR (RT-PCR), in situ PCR, quantitative PCR (Q-PCR),real-time quantitative PCR (RT Q-PCR), in situ hybridization, Southernblot, Northern blot, sequence analysis, microarray analysis, detectionof a reporter gene, or other DNA/RNA hybridization platforms.

In some embodiments, the level of nucleic acids encoding a gene in asample can be measured via a hybridization assay. In some embodiments,the hybridization assay comprises at least one binding partner. In someembodiments, the hybridization assay comprises at least oneoligonucleotide binding partner. In some embodiments, the hybridizationassay comprises at least one labeled oligonucleotide binding partner. Insome embodiments, the hybridization assay comprises at least one pair ofoligonucleotide binding partners. In some embodiments, the hybridizationassay comprises at least one pair of labeled oligonucleotide bindingpartners.

Any binding agent that specifically binds to a desired nucleic acid orprotein may be used in the methods and kits described herein to measurean expression level in a sample. In some embodiments, the binding agentis an antibody or an aptamer that specifically binds to a desiredprotein. In other embodiments, the binding agent may be one or moreoligonucleotides complementary to a nucleic acid or a portion thereof.In some embodiments, a sample may be contacted, simultaneously orsequentially, with more than one binding agent that binds differentproteins or different nucleic acids (e.g., multiplexed analysis).

To measure an expression level of a protein or nucleic acid, a samplecan be in contact with a binding agent under suitable conditions. Ingeneral, the term “contact” refers to an exposure of the binding agentwith the sample or cells collected therefrom for suitable periodsufficient for the formation of complexes between the binding agent andthe target protein or target nucleic acid in the sample, if any. In someembodiments, the contacting is performed by capillary action in which asample is moved across a surface of the support membrane.

In some embodiments, an assay may be performed in a low-throughputplatform, including single assay format. In some embodiments, an assaymay be performed in a high-throughput platform. Such high-throughputassays may comprise using a binding agent immobilized to a solid support(e.g., one or more chips). Methods for immobilizing a binding agent willdepend on factors such as the nature of the binding agent and thematerial of the solid support and may require particular buffers. Suchmethods will be evident to one of ordinary skill in the art.

Molecular Functional (MF) Expression Signatures

In some embodiments, determining the TME type of a subject (or abiological sample obtained from a subject) comprises determining amolecular functional (MF) expression signature (MFES) of the subject.

A “molecular functional expression signature (MFES)”, as describedherein, refers to information relating to molecular and cellularcomposition, and biological processes that are present within and/orsurrounding the tumor. For example, the information surrounding thetumor as disclosed herein may comprise factors contributing to a tumormicroenvironment as understood by a skilled person in the art. In someembodiments, biological processes comprise biological pathways thatencompass the genes provided in Table 3 in the instant application asunderstood by a skilled person in the art. In some embodiments,biological processes comprise biological pathways that encompass thegenes in any pathways that are relevant to TME.

In some embodiments, the MFES of a patient includes gene express scoresfor each of one or more groups of genes (“gene groups”). Thus, theinformation in the MFES may be generated using gene expression data (forexample sequencing data, e.g., using whole exome sequencing data, RNAsequencing data, or other gene expression data) for the gene groupsobtained by sequencing normal and/or tumor tissue. Examples of genegroups and techniques for determining gene group expression levels aredescribed in International PCT Publication WO2018/231771, the entirecontents of which are incorporated herein by reference. Aspects of thedisclosure are based, in part, on the use of MF expression signatures toidentify one or more (e.g., four) TME types in a biological sampleobtained from a subject, and determining whether the subject is acandidate for CAR T-cell therapy based on the TME type that isidentified.

A “gene group,” as described herein, refers to a group of genesassociated with related compositions and processes present within and/orsurrounding a tumor. For example, Angiogenesis gene group providesinformation related to blood vessel system composition and activitywithin a tumor. Examples of information related to blood vessel systemcomposition and activity within a tumor presented in the angiogenesisgene group include, but are not limited to, the number of blood vessels,the growth of lymphatic vessels, integrity of intercellular junctions ofendothelial cells, growth of microvascular endothelial cells, andvascular remodeling.

Exemplary signatures in a MF expression signature may include, but arenot limited to, Lymphatic endothelium (LEC), Angiogenesis (VEC),Cancer-associated fibroblasts (CAF), Fibroblastic reticular cells (FRC),Matrix (ECM), Matrix Remodeling (ECM remodeling), Granulocyte traffic,Protumor cytokines (IS cytokines), Follicular Dendritic Cells (FDC),Macrophages, M1 signature (activated M1), Effector cell traffic (T celltraffic), Major histocompatibility complex II (MHC-II), Majorhistocompatibility complex I (MHC-I), Follicular B helper T cells (TFH),Regulatory T cells (Treg), T cells (TIL), Checkpoint inhibition (IScheckpoints), Natural Killer Cells (NK cells), B cell traffic, Benign Bcells (B cells), and Tumor proliferation rate (cell proliferation).

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes as shown in thefollowing lists of gene groups. In some embodiments, the genes caninclude genes that across all gene groups in the following lists. Insome embodiments, the genes can include genes from one or more, but notall gene groups in the following lists. In some embodiments, the genescan include genes from one gene group in the following lists. In someembodiments all of the listed genes are selected from each group. Insome embodiments the numbers of genes in each selected group are not thesame, and at least one gene from each gene group is selected (e.g., 1,2, 3, 4, 5, or more genes in each gene group are selected): Lymphaticendothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21,FOXC2, EDNRB, LYVE1, PROX1, SOX18, JAM2; Angiogenesis (VEC): CDH5, PGF,PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR,VEGFB, ANGPT2; Cancer-associated fibroblasts (CAF): COL1A1, MMP2,LGALS1, MMP7, LRP1, CD248, S100A4, FAP, FGF2, MMP9, CTGF, ACTA2, FN1,COL1A2, COL5A1, COL6A1, MMP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3,MMP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2,TGFB2; Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E,VIM, PDPN, THY1, DES, VCAM1, PTGS2, LTBR; Matrix (ECM): COL1A1, COL3A1,LGALS7, FN1, VTN, COL1A2, COL4A1; Matrix Remodeling (ECM remodeling):TIMP1, TIMP2, MMP2, MMP9, CA9; Granulocyte traffic: KITLG, CXCL8, CXCR1,CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, CXCL2; Protumor cytokines (IScytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8, IL22, IL10; FollicularDendritic Cells (FDC): PDPN, TNFRSF1A, LTBR, FDCSP, CLU, PRNP, BST1;Macrophages: IL10, MSR1, ARG1, CSF1R, CD163, MRC1, CSF1; M1 signature(activated M1): TNF, NOS2, IL1B, CMKLR1; Effector cell traffic (T celltraffic): CXCL11, CXCL10, CXCL9, CXCR3, CX3CL1, CCL5, CX3CR1; Majorhistocompatibility complex II (MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1,HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, HLA-DMB; Major histocompatibilitycomplex I (MHC-I): TAP1, HLA-C, B2M, HLA-B, HLA-A, TAP2; Follicular Bhelper T cells (TFH): CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6,IL21, ICOS; Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3,IL10, TNFRSF18; T cells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28,CD3E, TRBC1, TRAC, CD3G; Checkpoint inhibition (IS checkpoints): CTLA4,HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, LAG3; Natural Killer Cells(NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG, GNLY,NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, KLRF1; B cell traffic:CXCL13, CXCR5, CCR6, CCL20; Benign B cells (B cells): CD79B, MS4A1,STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5, CD79A,TNFRSF13C, FCRL5; and Tumor proliferation rate (cell proliferation):MCM6, AURKB, ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2,E2F1, CETN3, CDK2, PLK1, BUB1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Lymphatic endothelium (LEC): JAM3, PPP1R13B, CXCL12,PDPN, CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, JAM2.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC,CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, ANGPT2.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Cancer-associated fibroblasts (CAF): COL1A1, WP2,LGALS1, WP7, LRP1, CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1,COL1A2, COL5A1, COL6A1, WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3,MMP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2,TGFB2.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Fibroblastic reticular cells (FRC): PDGFRA, ACTA2,ICAM1, NT5E, VIM, PDPN, THY1, DES, VCAM1, PTGS2, LTBR.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Matrix (ECM): COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, COL4A1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes)as shown in the following lists: Matrix Remodeling (ECM remodeling):TIMP1, TIMP2, WP2, WP9, CA9.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes) as shown in the following lists:Granulocyte traffic: KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11,CCR3, CXCL1, CXCL2.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Protumor cytokines (IS cytokines): CCL4, IL6, TNFSF13B, MIF,CXCL8, IL22, IL10.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A, LTBR, FDCSP,CLU, PRNP, BST1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Macrophages: IL10, MSR1, ARG1, CSF1R, CD163, MRC1, CSF1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes) as shown in thefollowing lists: M1 signature (activated M1): TNF, NOS2, IL1B, CMKLR1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Effector cell traffic (T cell traffic): CXCL11, CXCL10, CXCL9,CXCR3, CX3CL1, CCL5, CX3CR1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes) as shownin the following lists: Major histocompatibility complex II (MHC-II):HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1,HLA-DMB.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes) as shown in the following lists: Majorhistocompatibility complex I (MHC-I): TAP1, HLA-C, B2M, HLA-B, HLA-A,TAP2.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Follicular B helper T cells (TFH): CD40LG, SH2D1A,CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, ICOS.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes) as shown in the followinglists: Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3,IL10, TNFRSF18.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes) as shown in the following lists: T cells(TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC, CD3G.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes) as shownin the following lists: Checkpoint inhibition (IS checkpoints): CTLA4,HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, LAG3.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Natural Killer Cells (NK cells): SH2D1B, GZMH, GZMB,CD160, KLRK1, NCR3, CD244, IFNG, GNLY, NCR1, CD226, NKG7, EOMES, KLRC2,FGFBP2, KIR2DL4, KLRF1.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes) as shown in thefollowing lists: B cell traffic: CXCL13, CXCR5, CCR6, CCL20.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Benign B cells (B cells): CD79B, MS4A1, STAP1,TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5, CD79A, TNFRSF13C,FCRL5.

In some embodiments, the gene groups of the molecular-functional (MF)expression signature may comprise at least two genes (e.g., at least twogenes, at least three genes, at least four genes, at least five genes,at least six genes, at least seven genes, at least eight genes, at leastnine genes, at least ten genes, or more than ten genes) as shown in thefollowing lists: Tumor proliferation rate (cell proliferation): MCM6,AURKB, ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1,CETN3, CDK2, PLK1, BUB1.

In some embodiments, determining gene group expression scores for eachof the genes comprises determining the gene expression data that isavailable. For example, the available gene expression data may includeall genes in the gene sets as disclosed herein. In some embodiments, theavailable gene expression data may not include all genes in the genesets as disclosed herein.

In some embodiments, a molecular-functional signature is calculated byfirst performing single sample Gene Set Enrichment Analysis (ssGSEA) onexpression data to produce a plurality of gene group enrichment scores.Single sample GSEA (ssGSEA) is generally known in the art, for exampleas described by Barbie et al. Nature. 2009 Nov. 5; 462(7269): 108-112.In some embodiments, ssGSEA is performed according to the followingalgorithm:

${ssGSEA{score}} = {\frac{\sum\limits_{i}^{N}r_{i}^{1.25}}{\sum\limits_{i}^{N}r_{i}^{0.25}} - \frac{\left( {M - N + 1} \right)}{2}}$

-   -   r_(i)—rank of ith gene in expression matrix    -   N—number of genes in geneset    -   M—total number of genes in expression matrix

In some embodiments, the ssGSEA is performed on expression data from asubject. In some embodiments, a molecular-functional signature iscalculated by performing single sample Gene Set Enrichment Analysis(ssGSEA) on expression data from a plurality of subjects, for exampleexpression data from one or more cohorts of subjects in order to producea plurality of enrichment scores.

In some embodiments, ssGSEA is performed on expression data comprisingthree or more (e.g., 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, or 20) gene groups set forth in Table 3. In someembodiments, each of the gene groups separately comprises one or more(e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,55, 56, 57, 58, 59, 60, 61, 62, 63, 64, or more) genes listed in Table3. In some embodiments, a molecular-functional signature is produced byperforming ssGSEA on all 25 of the gene groups in Table 3, each genegroup including all listed genes in Table 3.

In some embodiments, one or more (e.g., a plurality) of enrichmentscores are normalized in order to produce a molecular-functionalsignature for the expression data (e.g., expression data of the subjector of a cohort of subjects). In some embodiments, the enrichment scoresare normalized by median scaling. In some embodiments, median scalingcomprises clipping the range of enrichment scores to about −4.0 to +4.0.In some embodiments, median scaling produces a molecular-functionalsignature of the subject.

The MFES of the subject may be associated with any of the tumormicroenvironment (TME) type clusters or lymphoma microenvironment (LME)type clusters described herein, for example in the sections entitled“Tumor Microenvironment (TME) Types” and “Lymphoma Microenvironment(LME) Types”. In some embodiments, the MFES of a subject is associatedwith a solid cancer TME type A cluster. In some embodiments, the MFES ofa subject is associated with a solid cancer TME type B cluster. In someembodiments, the MFES of a subject is associated with a solid cancer TMEtype C cluster. In some embodiments, the MFES of a subject is associatedwith a solid cancer TME type D cluster. In some embodiments, the MFES ofa subject is associated with a blood cancer TME type A cluster. In someembodiments, the MFES of a subject is associated with a blood cancer TMEtype B cluster. In some embodiments, the MFES of a subject is associatedwith a blood cancer TME type C cluster. In some embodiments, the MFES ofa subject is associated with a blood cancer TME type C cluster. In someembodiments, the lymphoma microenvironment (LME) signature of a subjectis associated with a lymphoma microenvironment (LME) type 1 (LME-B)cluster. In some embodiments, the LME signature of a subject isassociated with a lymphoma microenvironment (LME) type 2 (LME-C)cluster. In some embodiments, the LME signature of a subject isassociated with a lymphoma microenvironment (LME) type 3 (LME-A)cluster. In some embodiments, the LME signature of a subject isassociated with a lymphoma microenvironment (LME) type 4 (LME-D)cluster.

A subjects MFES or LME signature may be associated with one or multipleof the TME type clusters or LME type clusters in any suitable way. Forexample, a MFES may be associated with one of the TME type clustersusing a similarity metric (e.g., by associating the MFES with the TMEtype cluster whose centroid is closest to the MFES according to thesimilarity metric). As another example, a statistical classifier (e.g.,k-means classifier or any other suitable type of statistical classifier)may be trained to classify the MFES as belonging to one or multiple ofthe TME type clusters.

Lymphoma Microenvironment (LME) Signatures

In some embodiments, determining the LME type of a subject (or abiological sample obtained from a subject) comprises determining a LMEsignature of the subject.

Exemplary LME signatures may include, but are not limited to, geneexpression scores for the following gene groups: Lymphatic endothelium(LEC), Angiogenesis (VEC), Cancer-associated fibroblasts (CAF),Fibroblastic reticular cells (FRC), Matrix (ECM), Matrix Remodeling (ECMremodeling), Granulocyte traffic, Protumor cytokines (IS cytokines),Follicular Dendritic Cells (FDC), Macrophages, M1 signature (activatedM1), Effector cell traffic (T cell traffic), Major histocompatibilitycomplex II (MHC-II), Major histocompatibility complex I (MHC-I),Follicular B helper T cells (TFH), Regulatory T cells (Treg), T cells(TIL), Checkpoint inhibition (IS checkpoints), Natural Killer Cells (NKcells), B cell traffic, Benign B cells (B cells), and Tumorproliferation rate (cell proliferation). In some embodiments, a LMEsignature comprises one or more PROGENY pathway scores selected from thefollowing: Nuclear factor kappa B (NFkB), Phosphoinositide 3-kinase(PI3K), and p53.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes as shown in the following lists; in someembodiments all of the listed genes are selected from each group; and insome embodiments the numbers of genes in each selected group are not thesame). In some embodiments, the genes can include genes that across allgene groups in the following lists. In some embodiments, the genes caninclude genes from one or more, but not all gene groups in the followinglists. For example, in some embodiments, the genes can include at least75% of the genes across all gene groups in the following list. In someembodiments, the genes can include genes from one gene group in thefollowing lists.

The lists as disclosed herein comprise: Lymphatic endothelium (LEC):JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1,PROX1, SOX18, JAM2; Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC,CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, ANGPT2;Cancer-associated fibroblasts (CAF): COL1A1, WP2, LGALS1, WP7, LRP1,CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1,WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, WP12, MFAP5, MMP1,COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2, TGFB2; Fibroblasticreticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E, VIM, PDPN, THY1, DES,VCAM1, PTGS2, LTBR; Matrix (ECM): COL1A1, COL3A1, LGALS7, FN1, VTN,COL1A2, COL4A1; Matrix Remodeling (ECM remodeling): TIMP1, TIMP2, WP2,WP9, CA9; Granulocyte traffic: KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT,CCL11, CCR3, CXCL1, CXCL2; Protumor cytokines (IS cytokines): CCL4, IL6,TNFSF13B, MIF, CXCL8, IL22, IL10; Follicular Dendritic Cells (FDC):PDPN, TNFRSF1A, LTBR, FDCSP, CLU, PRNP, BST1; Macrophages: IL10, MSR1,ARG1, CSF1R, CD163, MRC1, CSF1; M1 signature (activated M1): TNF, NOS2,IL1B, CMKLR1; Effector cell traffic (T cell traffic): CXCL11, CXCL10,CXCL9, CXCR3, CX3CL1, CCL5, CX3CR1; Major histocompatibility complex II(MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA,HLA-DRB1, HLA-DMB; Major histocompatibility complex I (MHC-I): TAP1,HLA-C, B2M, HLA-B, HLA-A, TAP2; Follicular B helper T cells (TFH):CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, ICOS; RegulatoryT cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, TNFRSF18; Tcells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC,CD3G; Checkpoint inhibition (IS checkpoints): CTLA4, HAVCR2, CD274,PDCD1, BTLA, TIGIT, PDCD1LG2, LAG3; Natural Killer Cells (NK cells):SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG, GNLY, NCR1, CD226,NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, KLRF1; B cell traffic: CXCL13,CXCR5, CCR6, CCL20; Benign B cells (B cells): CD79B, MS4A1, STAP1,TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5, CD79A, TNFRSF13C,FCRL5; and Tumor proliferation rate (cell proliferation): MCM6, AURKB,ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3,CDK2, PLK1, BUB1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists:Lymphatic endothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4,CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, JAM2.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists:Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2,ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, ANGPT2.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists:Cancer-associated fibroblasts (CAF): COL1A1, WP2, LGALS1, WP7, LRP1,CD248, S100A4, FAP, FGF2, WP9, CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1,WP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, MMP12, MFAP5, MMP1,COL6A2, TIMP1, COL4A1, TGFB1, LUM, LGALS9, PTGS2, TGFB2.

In some embodiments, the gene groups of the LME expression signature maycomprise at least two genes (e.g., at least two genes, at least threegenes, at least four genes, at least five genes, at least six genes, atleast seven genes, at least eight genes, at least nine genes, at leastten genes, or more than ten genes) as shown in the following lists:Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E, VIM,PDPN, THY1, DES, VCAM1, PTGS2, LTBR.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Matrix (ECM): COL1A1,COL3A1, LGALS7, FN1, VTN, COL1A2, COL4A1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes) as shown in the following lists:Matrix Remodeling (ECM remodeling): TIMP1, TIMP2, WP2, MMP9, CA9.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes) as shown in the following lists: Granulocyte traffic: KITLG,CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, CXCL2.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Protumor cytokines (IScytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8, IL22, IL10.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Follicular Dendritic Cells(FDC): PDPN, TNFRSF1A, LTBR, FDCSP, CLU, PRNP, BST1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Macrophages: IL10, MSR1,ARG1, CSF1R, CD163, MRC1, CSF1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes) as shown in the following lists: M1 signature(activated M1): TNF, NOS2, IL1B, CMKLR1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Effector cell traffic (Tcell traffic): CXCL11, CXCL10, CXCL9, CXCR3, CX3CL1, CCL5, CX3CR1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes) as shown in the following lists:Major histocompatibility complex II (MHC-II): HLA-DQB1, HLA-DPB1,HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, HLA-DMB.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes) as shown inthe following lists: Major histocompatibility complex I (MHC-I): TAP1,HLA-C, B2M, HLA-B, HLA-A, TAP2.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten gene) as shown in the following lists:Follicular B helper T cells (TFH): CD40LG, SH2D1A, CD84, CXCR5, IL4,IL6, MAF, BCL6, IL21, ICOS.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes) as shown in the following lists: Regulatory T cells (Treg):CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, TNFRSF18.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes) as shown in the following lists: T cells (TIL): CD3D, TRAT1,TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC, CD3G.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes) as shown in the following lists:Checkpoint inhibition (IS checkpoints): CTLA4, HAVCR2, CD274, PDCD1,BTLA, TIGIT, PDCD1LG2, LAG3.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists: NaturalKiller Cells (NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244,IFNG, GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, KLRF1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes) as shown in the following lists: B cell traffic:CXCL13, CXCR5, CCR6, CCL20.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists: Benign Bcells (B cells): CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B,BLK, CD19, PAX5, CD79A, TNFRSF13C, FCRL5.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists: Tumorproliferation rate (cell proliferation): MCM6, AURKB, ESCO2, CCNB1,AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, BUB1.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists: Nuclearfactor kappa B (NFkB): PROGENY pathway score.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists:Phosphoinositide 3-kinase (PI3K): PROGENY pathway score.

In some embodiments, the gene groups of the LME signature may compriseat least two genes (e.g., at least two genes, at least three genes, atleast four genes, at least five genes, at least six genes, at leastseven genes, at least eight genes, at least nine genes, at least tengenes, or more than ten genes) as shown in the following lists: p53:PROGENY pathway score.

Tumor Microenvironment (TME) Types

The disclosure is based, in part, on the recognition that CAR T-celltherapy (or combination therapies that include CAR T-cells) is likely tobe more effective (or not effective) in subjects having certain TMEtypes than subjects having other TME types. In some embodiments, a bloodcancer or lymphoma TME type is selected from type A, type B, type C, andtype D.

In some embodiments, the disclosure provides determining whether thesubject is likely to respond to an adoptive cell transfer therapy (e.g.,CAR T-cell therapy) using the identified TME subtype. In someembodiments, the disclosure provides identifying, from among a pluralityof TME types as disclosed herein, whether the subject is likely torespond to an adoptive cell transfer therapy (e.g., CAR T-cell therapy).In some embodiments, the plurality of TME types may be associated withdifferent likelihoods of response to adoptive cell transfer therapy.

In some embodiments, a subject having a blood cancer or lymphoma type“A” is characterized by an immuno-suppressive TME. In some embodiments,a blood cancer or lymphoma type A TME comprises macrophages thatsuppress T-cell function and/or a high percentage (e.g., relative to anon-tumor microenvironment or other TME types) of exhausted T-cells. Insome embodiments, subject having blood cancer or lymphoma type A areexpected to be resistant to treatment with CAR T-cell therapies that arenot resistant to T-cell exhaustion or suppressive environments, such asCAR T-cell monotherapies (e.g., CAR T-cells that do not express anyadditional co-factors, such as immunomodulators or immune checkpointinhibitors). In some embodiments, CAR T-cell therapies that areresistant to high acidosis levels are expected to be therapeuticallyeffective in subjects having blood cancer or lymphoma TME type A. Insome embodiments, combinations of CAR T-cell therapies with immunecheckpoint inhibitors are expected to be therapeutically effective insubjects having blood cancer or lymphoma TME type A.

In some embodiments, a subject having a blood cancer or lymphoma type“B” is characterized by having genotypes and/or phenotypes close tonormal cells. In some embodiments, a blood cancer or lymphoma type B TMEis characterized by an increased number of CD4+, Follicular helperT-cells (Tfh), and, in certain cancers, lymphatic endothelium, relativeto non-tumor microenvironments or other TME types. In some embodiments,blood cancer or lymphoma type B TME is characterized by a low tumorcontent and a high percentage of non-malignant B-cells. In someembodiments, blood cancer or lymphoma type B TME comprises a highpercentage of HVEM, CD83, STATE, and/or FOXO1 mutations (e.g., relativeto non-tumor microenvironments or other TME types). In some embodiments,tumors or cancer cells of blood cancer or lymphoma type B are expectedto respond to chemotherapy, for example Rituximab. In some embodiments,subjects having blood cancer or lymphoma type B are expected to respondto CAR-T therapy that targets cancer cell surface ligands (e.g., if CD19is expressed on the surface then a CAR T-cell therapy targeting CD19 isexpected to provide a therapeutic benefit). In some embodiments, bloodcancer or lymphoma type B TME subjects are responsive to CAR T-cellmonotherapies (e.g., CAR T-cells that do not express any additionalco-factors, such as immunomodulators or immune checkpoint inhibitors).

In some embodiments, blood cancer or lymphoma type “C” is characterizedby a TME enriched with fibroblasts, stromal cells, follicular dendriticand reticular cells (e.g., relative to non-tumor microenvironments orother TME types). In some embodiments, cancer cells in blood cancer orlymphoma type C are highly vascularized (e.g., relative to cancer cellsin other TME types). In some embodiments, blood cancer or lymphoma typeC TME is characterized by low lymphocyte and macrophage infiltration.Examples of cancers having type C TME include non-Hodgkins lymphomas,such as Diffuse Large B cell lymphoma (DLBCL), Follicular Lymphoma (FL)and Mantle cell lymphoma (MCL). In some embodiments, subjects havingblood cancer or lymphoma type C TME cancers are expected to respond toimmune checkpoint inhibitors. CAR T-cell therapies administered incombination with immune checkpoint inhibitors are expected to betherapeutically effective. In some embodiments, blood cancer or lymphomatype C TME subjects are not responsive to CAR T-cell monotherapies(e.g., CAR T-cells that do not express any additional co-factors, suchas immunomodulators or immune checkpoint inhibitors).

In some embodiments, blood cancer or lymphoma type “D” is characterizedby an immune cell depleted TME having a low number of immune and stromalinfiltrates, and a CD4/CD8 bias towards CD8+ cells. In some embodiments,blood cancer or lymphoma type D TME is characterized as having a highertumor content and higher percentage of relapsed/refractory cases thanother types. In some embodiments, tumors or cancer cells in a bloodcancer or lymphoma type D TME are hypermethylated, aneuploid orpolyploid, and/or comprise a high mutation load and/or a highcirculating nucleic acid (CNA) load. In the context of lymphomas,examples of type D TME is found in double hit cancers, for exampleDHITsig+ cases. In some embodiments, CAR T-cell therapy is not expectedto have a therapeutic benefit for subject having blood cancer orlymphoma type D TME because certain tumors in this TME are not dependenton B cell receptors, and NFkB intrinsically activated tumors are notexpected to respond to CAR T-cell therapy. In some embodiments, CART-cell therapy may be expected to be effective in subjects having bloodcancer or lymphoma type D cancers characterized by PI3K-dependentMYC-negative cancer cells. In some embodiments, CAR T-cell therapies maysynergize with certain chemotherapies (e.g., Ibrutinib and other BTKinhibitors) in a type D TME.

In some embodiments, a solid tumor cancer TME type is selected from typeA, type B, type C, and type D. In some embodiments, solid tumor cancertype A comprises an inflamed/vascularized, and/or inflamed/fibroblastenriched TME. In some embodiments, solid tumor cancer type B comprisesan inflamed/non-vascularized, and/or inflamed/non-fibroblast enrichedTME. In some embodiments, solid tumor cancer type C comprises anon-inflamed/vascularized, and/or non-inflamed/fibroblast enriched TME.In some embodiments, solid tumor cancer type D comprises anon-inflamed/non-vascularized, and/or non-inflamed/non-fibroblastenriched TME. In some embodiments, a solid tumor type D TME is alsoreferred to as an “immune desert” type.

In some embodiments, an adoptive cell therapy can be used for treating asolid tumor cancer in a subject who has been determined as likely torespond to the adoptive cell therapy.

In some embodiments, an adoptive cell therapy can be used for treating asolid tumor cancer in a subject who has been determined as having a typeA TME, a type B TME, or a type D TME.

In some embodiments, a therapeutic agent can be used for treating asolid tumor cancer in a subject who has been determined as unlikely torespond to the CAR T-cell therapy.

In some embodiments, a therapeutic agent can be used for treating asolid tumor cancer in a subject who has been determined as having a typeC TME.

As used herein, “inflamed” refers to the level of compositions andprocesses related to inflammation in a cancer (e.g., a tumor). In someembodiments, inflamed cancers (e.g., tumors) are highly infiltrated byimmune cells, and are highly active with regard to antigen presentationand T-cell activation.

As used herein, “vascularized” refers to the formation of blood vesselsin a cancer (e.g., a tumor). In some embodiments, vascularized cancers(e.g., tumors) comprise high levels of cellular compositions and processrelated to blood vessel formation.

As used herein, “fibroblast enriched” refers to the level or amount offibroblasts in a cancer (e.g., a tumor). In some embodiments, fibroblastenriched tumors comprise high levels of fibroblast cells.

In some embodiments, a solid tumor cancer (or blood or lymphoma) TMEtype is determined by a method described, for example in InternationalPCT Publication WO2018/231771.

In some embodiments, methods further comprise determining whether asubject has a cancer type (e.g., a lymphoma type) selected from EZB,A53, BN2, EZB; MCD; N1; ST2 and/or MYC+, for example as described byWright et al. Cancer Cell. 2020 Apr. 13; 37(4):551-568.e14. In someembodiments, subjects that are EZB, A53, and/or MYC+ are not expected torespond to CAR T-cell therapy. Accordingly, in some embodiments,subjects that are EZB, A53, and/or MYC+ are administered a treatmentthat does not include a CAR-T cell therapy.

Turning to the Figures, FIG. 1A provides a description of one example ofa process for using a computer hardware processor to perform a method ofidentifying the tumor microenvironment (TME) type of a subject,according to some aspects of the invention 100. First, sequencing datafrom a biological sample obtained from a subject is obtained 102.Methods of obtaining sequencing data are described throughout thespecification including in the section entitled Sequencing Data and GeneExpression Data. Next, the sequencing data is processed to obtain geneexpression data 104. Gene expression data is used to determine amolecular-functional expression signature (MFES) using the geneexpression data for the subject 106. In some embodiments, thedetermining comprises processing the gene expression data to producegene enrichment scores for gene groups (e.g., processing by singlesample GSEA) 108. In some embodiments, the determining comprisesprocessing of gene expression data to produce molecular-functionalexpression signatures (MFES) 110. In some embodiments, the determiningcomprises identifying a TME type based on MFES 112. In some embodiments,the method includes determining whether a subject is likely to respondto adoptive cell transfer therapy based on TME type 114. In someembodiments, the method comprises administering the identified therapy116.

Employing such TME type selection techniques provides an improvement topatient selection technology. Selection of patients likely to respond toCAR-T therapy based upon TME type as described herein has severaladvantages. First, it provides physicians increased confidence inprescribing CAR-T therapy to certain populations of patients that maynot have a high response rate to first-line therapeutics (e.g.,rituximab). Furthermore, it helps the patients who are unlikely torespond well to a CAR-T therapy avoid the costs and inconvenience ofreceiving a CAR-T therapy, and to focus on exploring alternativetreatments. Second, classification of patients by TME type may improveclinical trial design and efficiency by allowing selection of patientswho are likely to respond to CAR-T therapy, and excluding subjectshaving TME types indicative of a lower response to CAR-T therapy.

Lymphoma Microenvironment (LME) Types

The disclosure is based, in part, on the determination of a lymphomamicroenvironment (LME) type of a subject according to a LME signature ofthe subject. In some embodiments, the subject is a mammal. In someembodiments, the subject is a human.

B cell lymphomas are cancers that arise from cells that depend onnumerous highly orchestrated interactions with immune and stromal cells.In addition, the progress of B cell lymphomas relies on interactionswith the non-malignant cells and stromal elements that constitute thetumor microenvironment. DLBCL is a common type of high-grade non-Hodgkinlymphoma that develops from the abnormal B cells in the lymphaticsystem. In some embodiments, the DLBCL is Activated B cell (ABC) DLBCL.In some embodiments, the DLBCL is Germinal center B cell-like (GCB)DLBCL. In some cases, a subject may have a rare type of DLBCL. Forexample, rare types of DLBCL may include EBV-positive DLBCL nototherwise specified.

In some embodiments, LME types includes LME-A type, LME-B type, LME-Ctype, and LME-D type. In some embodiments, LME-A type, LME-B type, LME-Ctype, and LME-D type represent the lymphoma microenvironments of DLBCL.In some embodiments, DLBCL may comprise other LME types not otherwisespecified.

Without wishing to be bound by any theory, the tumor microenvironment ofB cell lymphomas may contain variable numbers of immune cells, stromalcells, blood vessels and extracellular matrix. In some embodiments,LME-B type of DLBCL is characterized by an “immunosuppressive”microenvironment enriched for T regulatory cells, myeloid-derivedsuppressor cells, CD8^(PD1high) natural killer and macrophages type 2,and prevalence of genetic mechanisms of immune escape in malignant cellssuch as mutations in B2M and CD70. In some embodiments, malignant cellsin LME-B DLBCL present high activity of NF-kB and JAK/STAT signalingpathways. Without wishing to be bound by any theory, it likely due tohigh frequency of co-occurring MYD88^(L265) and CD79B mutations and thepresence of a cytokine rich milieu including high expression of IL10,IL6 and TNFS13B.

In some embodiments, LME-C type of DLBCL is characterized by an“anti-tumor immunity” microenvironment enriched for T cells, follicularT_(H) and follicular dendritic cells (FDC). In some embodiments, LME-CDLBCL presents the highest number of BCL2 translocations, EZH2mutations, activation of cell motility, and chemotaxis pathways relativeto other LME types. In some embodiments, lymphoma cells of LME-C DLBCLexpress higher levels of CCL20, CCR6 and CXCR5.

In some embodiments, LME-A type of DLBCL is characterized by a“mesenchymal” microenvironment enriched for cancer-associatedfibroblasts (CAFs), reticular dendritic cells (DC), FDC, and endothelialcells. In some embodiments, lymphoma cells of LME-A type of DLBCL showhigher mutations in BCR/Pi3K signaling intermediates SGK1 and GNA13 andactivation of the TGFB signaling and matrix remodeling pathways. Inaddition, LME-A DLBCL expresses higher levels of MMP9, MMP2, TIMP1 andTIMP2 than other LME types. LME-A DLBCL also has a higher proportion ofnon-cellular LME component represented by the extracellular matrix(ECM).

In some embodiments, LME-D type of DLBCL is characterized by a“depleted” microenvironment with an increased proportion of lymphomacells with mutations in MYD88, PIM1 and HLA-C, and higher genomicinstability and epigenetic heterogeneity (e.g., by DNA methylation).Lymphoma cells of LME-D DLBCL show activation of Pi3K signaling andhypermethylation and low expression of the TGFB mediator SMAD1.

In some aspects, the present disclosure provides methods for determininga DLBCL microenvironment LME type of a subject comprising obtainingsequencing data for a subject having, suspected of having, or at risk ofhaving a DLBCL. A subject having, suspected of having, or at risk ofhaving a DLBCL can be identified or diagnosed by routine examination orreview of family history, as would be understood by one of ordinaryskill in the art.

In some embodiments, the sequence data, as used herein, can include butare not limited to DNA or RNA data.

In some embodiments, the methods comprise determining a LME signaturefor the subject using the sequencing data. In some embodiments, the LMEsignature can be obtained by using (i) a gene expression signaturecomprising a plurality of gene group expression scores for a respectiveplurality of gene groups; and/or (ii) one or more PROGENY pathway scoresfor the sequencing data; and assigning, from a plurality of LME types,an LME type to the subject using the LME signature. In some embodiments,a plurality of gene group expression scores for a respective pluralityof gene groups can be obtained by obtaining a score for each of theplurality of groups and combining these into a LME expression signature.In some embodiments, the plurality of gene groups includes at leastthree of the gene groups from Table 3. In some embodiments, the LMEsignatures for the subjects comprise determining gene group expressionscores for the genes identified in Table 3. The gene groups and theirrespective gene group genes are described in the present disclosure.

In some embodiments, the present disclosure provides a method forproviding a prognosis, predicting survival or stratifying patient riskof a subject suspected of having, or at risk of having a Diffuse Large Bcell lymphoma (DLBCL). In some embodiments, the method comprisesdetermining a DLBCL microenvironment (LME) type of the subject asdescribed herein.

In some embodiments, the PROGENY pathway scores for the sequencing datacomprise NFkB, PI3K, and/or p53 signaling signatures. Without wishing tobe bound by any theory, the NFkB, PI3K, and/or p53 signaling signaturesare as understood by a skilled person in the art.

In some embodiments, the assigning comprises associating the LMEsignature of the subject with a cluster previously determined LMEsignatures selected from a LME-B type cluster, LME-C type cluster, LME-Atype cluster, and LME-D type cluster. In some embodiments, LMEsignatures can be any genetic signatures identified by the Applicant orin the art.

In some embodiments, the methods further comprise identifying thesubject as having a decreased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the subject isassigned type LME-C or LME-A. In some embodiments, “PFS24” representsprogression-free survival at 24 months. PFS indicates the time from thestart of evaluation to the earliest occurrence of progressive disease,relapse, or death. In some embodiments, a “decreased chance of a PFS24event” indicates that a subject is at least 10%, 20%, 30%, 40%, 50%,60%, 70%, 80%, 90%, or 100% less likely to experience a progression-freesurvival event (e.g., relapse, retreatment, or death) than anothercancer patient or population of cancer patients (e.g., patients havingthe same cancer, such as lymphoma, but not the same LME type as thesubject).

In some embodiments, the methods further comprise identifying thesubject as having an increased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the subject isassigned type LME-D. In some embodiments, an “increased chance of aPFS24 event” indicates that a subject is at least 10%, 20%, 30%, 40%,50%, 60%, 70%, 80%, 90%, or 100% more likely to experience aprogression-free survival event (e.g., relapse, retreatment, or death)than another cancer patient or population of cancer patients (e.g.,patients having the same cancer, such as lymphoma, but not the same LMEtype as the subject).

In some embodiments, the methods further comprise obtaining anInternational Prognostic Index (IPI) score of the subject. In someembodiments, the IPI is a score designated for the subjects who may havenon-Hodgkins lymphoma. The IPI is used for predicting outcomes inpatients with aggressive non-Hodgkins lymphoma on the basis of thesubjects'clinical characteristics before treatment. In some embodiments,the WI score is Low, Intermediate, or High. In some embodiments, theclassification of the IPI score can depend on the number of riskfactors.

In some embodiments, the methods further comprise identifying thesubject as having a decreased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the DLBCL istype LME-C ABC and the IPI score is High. In some embodiments, themethods further comprise identifying the subject as having an increasedchance of a PFS24 event (e.g., relapse, retreatment, or death) relativeto other LME types when the DLBCL is type LME-D GCB and the IPI score isHigh. In some embodiments, the methods further comprise identifying thesubject as having an increased chance of a PFS24 event (e.g., relapse,retreatment, or death) relative to other LME types when the DLBCL istype LME-A or LME-D ABC and the IPI score is Intermediate.

In some embodiments, the methods further comprise providing arecommendation to administer one or more immunotherapeutic agents to thesubject. In some embodiments, the one or more immunotherapeutic agentscomprises Rituximab.

In some embodiments, the methods described herein comprise the use of atleast one computer hardware processor to perform the determination.

In some aspects, the present disclosure provides methods for treating asubject having Diffuse Large B cell lymphoma (DLBCL). In someembodiments, the method comprises administering to a subject having beenidentified as having DLBCL characterized by a type LME-C or type LME-Aone or more immunotherapeutic agents. In some embodiments, the one ormore immunotherapeutic agents include any immunotherapeutic agents asdisclosed herein.

In some embodiments, the subject has been identified as having a typeLME-C or type LME-A by a method comprising: using at least one computerhardware processor to perform: obtaining sequencing data for a subjecthaving, suspected of having, or at risk of having a DLBCL. The methodscomprise determining a LME signature for the subject using thesequencing data, wherein the LME signature is obtained using: (i) a geneexpression signature comprising a plurality of gene group expressionscores for a respective plurality of gene groups; and/or (ii) one ormore PROGENY pathway scores for the sequencing data. In someembodiments, the methods comprise assigning, from a plurality of LMEtypes, an LME type to the subject using the LME signature. In someembodiments, a plurality of gene group expression scores for arespective plurality of gene groups can be obtained by obtaining a scorefor each of the plurality of groups and combining these into a LMEexpression signature.

FIG. 1B provides a description of one example of a process for using acomputer hardware processor to perform a method of identifying thelymphoma microenvironment (LME) type of a subject, according to someaspects of the invention 200. First, sequencing data from a biologicalsample obtained from a subject is obtained 202. Methods of obtainingsequencing data are described throughout the specification including inthe section entitled Sequencing Data and Gene Expression Data. Next, thesequencing data is processed to obtain gene expression data 204. Geneexpression data is used to determine a lymphoma microenvironmentsignature for the subject 206. In some embodiments, the determiningcomprises processing the gene expression data to produce gene expressionscores for gene groups 208. In some embodiments, processing of geneexpression data to produce lymphoma microenvironment signature comprisesusing Gene Group Expression Scores and PROGENY pathway scores on one ormore gene groups, for example the gene groups listed in Table 3 210. Insome embodiments, the determining comprises identifying LME types 212.In some embodiments, the method assigning a LME type to the subjectusing the identified LME signature 214. In some embodiments, the methodcomprises providing recommendation to administer one or moreimmunotherapeutic agents based on the LME type 216.

Employing such LME type selection techniques provides an improvement topatient categorization technology. Categorizing patients based upon LMEtype as described herein has several advantages. First, it providesphysicians increased confidence in providing a prognosis (e.g., asrelates to PFS24) or recommending particular therapeutic agents tocertain populations of patients that may not otherwise identifiable.Second, classification of patients by LME type may improve clinicaltrial design and efficiency by allowing selection of patients who arelikely to respond to therapeutic interventions, and excluding subjectshaving LME types indicative of a lower response to therapeuticintervention.

Combination Approach

In some aspects, methods disclosed herein may comprise determining atumor microenvironment (TME) type and a Diffuse Large B cell lymphoma(DLBCL) microenvironment (LME) type of a subject. The disclosure isbased, in part, on the determination of a lymphoma microenvironment(LME) type of a subject according to a LME signature of the subject andthe determination of a TME type of a subject (or a biological sampleobtained from a subject).

In some embodiments, the determination of a TME type comprisesdetermining a molecular functional (MF) expression signature (MFES) ofthe subject. In some embodiments, determining the LME type of a subject(or a biological sample obtained from a subject) comprises determining aLME signature of the subject.

In some embodiments, the methods disclosed herein comprise using atleast one computer hardware processor to obtaining sequencing data for asubject having, suspected of having, or at risk of having a solid tumorcancer, a blood cancer, and/or a DLBCL. In some embodiments, the subjectmay have more than one type of cancer. In some embodiments, the methodscomprise determining a molecular-functional (MF) expression signatureand a LME signature for the subject using the sequencing data. In someembodiments, the methods comprise identifying, from among tumormicroenvironment (TME) types, a TME type associated with the cancerusing the determined ME expression signature for the subject andobtaining the LME signature. In some embodiments, the LME signature canbe obtained by using (i) a gene expression signature comprising aplurality of gene group expression scores for a respective plurality ofgene groups; and/or (ii) one or more PROGENY pathway scores for thesequencing data; and assigning, from a plurality of LME types, an LMEtype to the subject using the LME signature.

In some embodiments, the methods disclosed herein comprise determiningwhether the subject is likely to respond to an adoptive cell transfertherapy based on the identified TME type. In some embodiments, themethods disclosed herein comprise determining a prognosis based at leastin part on the identified LME type, and providing a recommendation forthe administration of an immunotherapeutic agent. In some embodiments,the identified LME types in a subject may determine whether the subjectis likely to respond to an adoptive cell transfer therapy.

In some embodiments, the methods disclosed herein comprise treating asubject having Diffuse Large B cell lymphoma (DLBCL) or other types ofblood cancer.

In some embodiments, the tumor microenvironment (TME) types and theDiffuse Large B cell lymphoma (DLBCL) microenvironment (LME) types aredisclosed herein.

In some embodiments, the subject is a mammal. In some embodiments, thesubject is a human.

Reports

In some aspects, methods disclosed herein comprise generating a reportfor assisting with the preparation of recommendation for treatment. Thegenerated report can provide summary of information, so that theadminister can identify suitable therapy. The report as described hereinmay be a paper report, an electronic record, or a report in any formatthat is deemed suitable in the art. The report may be shown and/orstored on a computing device known in the art (e.g., handheld device,desktop computer, smart device, website, etc.). The report may be shownand/or stored on any device that is suitable as understood by a skilledperson in the art.

In some embodiments, methods disclosed herein can be used for commercialdiagnostic purposes. For example, the generated report may include butis limited to information concerning expression levels of one or moregenes from any of the gene groups described herein, clinical andpathologic factors, patients prognostic analysis, predicted response tothe treatment, classification of the tumor environment or lymphomaenvironment, the alternative treatment recommendation, and/or otherinformation. In some embodiments, the methods and reports may includedatabase management for the keeping of the generated reports. Forinstance, the methods as disclosed herein can create a record in adatabase for the subject (e.g., subject 1, subject 2, etc.) and populatethe specific record with data for the subject. In some embodiments, thegenerated report can be provided to the subject and/or to theclinicians. In some embodiments, a network connection can be establishedto a server computer that includes the data and report for receiving oroutputting. In some embodiments, the receiving and outputting of thedate or report can be requested from the server computer.

Therapeutic Methods

Molecular-functional (MF) expression signatures (MFES), in someembodiments, provide information relating to patient treatment. In someembodiments, molecular-functional (MF) expression signature providesinformation relating to an expected treatment outcome of a therapy. Insome embodiments, the molecular-functional (MF) expression signatureindicates that a specific treatment option is recommended. In someembodiments, the molecular-functional (MF) expression signatureindicates that a specific treatment option is non-curative. In someembodiments, the molecular-functional (MF) expression signatureindicates that a specific treatment option is dependent on a certainfeature of a tumor, for example, tumor microenvironment (TME) types ofthe tumor. In some embodiments, a subject is administered a therapeutic(e.g., a CAR-T therapy, chemotherapy, etc.) based upon a determinationof a subjects TME type or LME type. “Based on a determination” generallyrefers to 1) administering a particular therapy (e.g., CAR-T therapy) toa subject if or when the subject is determined to have a particular TMEtype, and/or 2) not administering a particular therapy (e.g., a CAR-Ttherapy) to a subject if or when the subject is determined to have aparticular TME type.

Aspects of the disclosure relate to methods of treating a subject having(or suspected or at risk of having) cancer based upon a determination ofthe TME type of the subject. In some embodiments, the methods compriseadministering one or more (e.g., 1, 2, 3, 4, 5, or more) therapeuticagents to the subject. In some embodiments, the therapeutic agent (oragents) administered to the subject are selected from small molecules,peptides, nucleic acids, radioisotopes, cells (e.g., CAR T-cells, etc.),and combinations thereof. Examples of therapeutic agents includechemotherapies (e.g., cytotoxic agents, etc.), immunotherapies (e.g.,immune checkpoint inhibitors, such as PD-1 inhibitors, PD-L1 inhibitors,etc.), antibodies (e.g., anti-HER2 antibodies), cellular therapies (e.g.CAR T-cell therapies), gene silencing therapies (e.g., interfering RNAs,CRISPR, etc.), antibody-drug conjugates (ADCs), and combinationsthereof.

In some embodiments, a subject is administered an effective amount of atherapeutic agent. “An effective amount” as used herein refers to theamount of each active agent required to confer therapeutic effect on thesubject, either alone or in combination with one or more other activeagents. Effective amounts vary, as recognized by those skilled in theart, depending on the particular condition being treated, the severityof the condition, the individual patient parameters including age,physical condition, size, gender and weight, the duration of thetreatment, the nature of concurrent therapy (if any), the specific routeof administration and like factors within the knowledge and expertise ofthe health practitioner. These factors are well known to those ofordinary skill in the art and can be addressed with no more than routineexperimentation. It is generally preferred that a maximum dose of theindividual components or combinations thereof be used, that is, thehighest safe dose according to sound medical judgment. It will beunderstood by those of ordinary skill in the art, however, that apatient may insist upon a lower dose or tolerable dose for medicalreasons, psychological reasons, or for virtually any other reasons.

Empirical considerations, such as the half-life of a therapeuticcompound, generally contribute to the determination of the dosage. Forexample, antibodies that are compatible with the human immune system,such as humanized antibodies or fully human antibodies, may be used toprolong half-life of the antibody and to prevent the antibody beingattacked by the hosts immune system. Frequency of administration may bedetermined and adjusted over the course of therapy, and is generally(but not necessarily) based on treatment, and/or suppression, and/oramelioration, and/or delay of a cancer. Alternatively, sustainedcontinuous release formulations of an anti-cancer therapeutic agent maybe appropriate. Various formulations and devices for achieving sustainedrelease are known in the art.

In some embodiments, dosages for an anti-cancer therapeutic agent asdescribed herein may be determined empirically in individuals who havebeen administered one or more doses of the anti-cancer therapeuticagent. Individuals may be administered incremental dosages of theanti-cancer therapeutic agent. To assess efficacy of an administeredanti-cancer therapeutic agent, one or more aspects of a cancer (e.g.,tumor microenvironment, tumor formation, tumor growth, or cancer ortumor microenvironment (TME) types A-D, lymphoma microenvironment (LME)types LME1-LME4, etc.) may be analyzed.

Generally, for administration of any of the anti-cancer antibodiesdescribed herein, an initial candidate dosage may be about 2 mg/kg. Forthe purpose of the present disclosure, a typical daily dosage mightrange from about any of 0.1 μg/kg to 3 μg/kg to 30 μg/kg to 300 μg/kg to3 mg/kg, to 30 mg/kg to 100 mg/kg or more, depending on the factorsmentioned above. For repeated administrations over several days orlonger, depending on the condition, the treatment is sustained until adesired suppression or amelioration of symptoms occurs or untilsufficient therapeutic levels are achieved to alleviate a cancer, or oneor more symptoms thereof. An exemplary dosing regimen comprisesadministering an initial dose of about 2 mg/kg, followed by a weeklymaintenance dose of about 1 mg/kg of the antibody, or followed by amaintenance dose of about 1 mg/kg every other week. However, otherdosage regimens may be useful, depending on the pattern ofpharmacokinetic decay that the practitioner (e.g., a medical doctor)wishes to achieve. For example, dosing from one-four times a week iscontemplated. In some embodiments, dosing ranging from about 3 μg/mg toabout 2 mg/kg (such as about 3 μg/mg, about 10 μg/mg, about 30 μg/mg,about 100 μg/mg, about 300 μg/mg, about 1 mg/kg, and about 2 mg/kg) maybe used. In some embodiments, dosing frequency is once every week, every2 weeks, every 4 weeks, every 5 weeks, every 6 weeks, every 7 weeks,every 8 weeks, every 9 weeks, or every 10 weeks; or once every month,every 2 months, or every 3 months, or longer. The progress of thistherapy may be monitored by conventional techniques and assays and/or bymonitoring tumor microenvironment (TME) types A-D, or lymphomamicroenvironment (LME) types 1-4, as described herein. The dosingregimen (including the therapeutic used) may vary over time.

When the anti-cancer therapeutic agent is not an antibody, it may beadministered at the rate of about 0.1 to 300 mg/kg of the weight of thepatient divided into one to three doses, or as disclosed herein. In someembodiments, for an adult patient of normal weight, doses ranging fromabout 0.3 to 5.00 mg/kg may be administered. The particular dosageregimen, e.g., dose, timing, and/or repetition, will depend on theparticular subject and that individuals medical history, as well as theproperties of the individual agents (such as the half-life of the agent,and other considerations well known in the art).

For the purpose of the present disclosure, the appropriate dosage of ananti-cancer therapeutic agent will depend on the specific anti-cancertherapeutic agent(s) (or compositions thereof) employed, the type andseverity of cancer, whether the anti-cancer therapeutic agent isadministered for preventive or therapeutic purposes, previous therapy,the patients clinical history and response to the anti-cancertherapeutic agent, and the discretion of the attending physician.Typically the clinician will administer an anti-cancer therapeuticagent, such as an antibody, until a dosage is reached that achieves thedesired result.

Administration of an anti-cancer therapeutic agent can be continuous orintermittent, depending, for example, upon the recipients physiologicalcondition, whether the purpose of the administration is therapeutic orprophylactic, and other factors known to skilled practitioners. Theadministration of an anti-cancer therapeutic agent (e.g., an anti-cancerantibody) may be essentially continuous over a preselected period oftime or may be in a series of spaced dose, e.g., either before, during,or after developing cancer.

As used herein, the term “treating” refers to the application oradministration of a composition including one or more active agents to asubject, who has a cancer, a symptom of a cancer, or a predispositiontoward a cancer, with the purpose to cure, heal, alleviate, relieve,alter, remedy, ameliorate, improve, or affect the cancer or one or moresymptoms of the cancer, or the predisposition toward a cancer.

Alleviating a cancer includes delaying the development or progression ofthe disease, or reducing disease severity. Alleviating the disease doesnot necessarily require curative results. As used therein, “delaying”the development of a disease (e.g., a cancer) means to defer, hinder,slow, retard, stabilize, and/or postpone progression of the disease.This delay can be of varying lengths of time, depending on the historyof the disease and/or individuals being treated. A method that “delays”or alleviates the development of a disease, or delays the onset of thedisease, is a method that reduces probability of developing one or moresymptoms of the disease in a given time frame and/or reduces extent ofthe symptoms in a given time frame, when compared to not using themethod. Such comparisons are typically based on clinical studies, usinga number of subjects sufficient to give a statistically significantresult.

“Development” or “progression” of a disease means initial manifestationsand/or ensuing progression of the disease. Development of the diseasecan be detected and assessed using clinical techniques known in the art.Alternatively, or in addition to the clinical techniques known in theart, development of the disease may be detectable and assessed based onother criteria. However, development also refers to progression that maybe undetectable. For purpose of this disclosure, development orprogression refers to the biological course of the symptoms.“Development” includes occurrence, recurrence, and onset. As used herein“onset” or “occurrence” of a cancer includes initial onset and/orrecurrence.

Examples of the antibody anti-cancer agents include, but are not limitedto, alemtuzumab (Campath), trastuzumab (Herceptin), Ibritumomab tiuxetan(Zevalin), Brentuximab vedotin (Adcetris), Ado-trastuzumab emtansine(Kadcyla), blinatumomab (Blincyto), Bevacizumab (Avastin), Cetuximab(Erbitux), ipilimumab (Yervoy), nivolumab (Opdivo), pembrolizumab(Keytruda), atezolizumab (Tecentriq), avelumab (Bavencio), durvalumab(Imfinzi), and panitumumab (Vectibix).

Examples of an immunotherapy include, but are not limited to, a PD-1inhibitor or a PD-L1 inhibitor, a CTLA-4 inhibitor, adoptive celltransfer, therapeutic cancer vaccines, oncolytic virus therapy, T-celltherapy, and immune checkpoint inhibitors.

Examples of radiation therapy include, but are not limited to, ionizingradiation, gamma-radiation, neutron beam radiotherapy, electron beamradiotherapy, proton therapy, brachytherapy, systemic radioactiveisotopes, and radiosensitizers.

Examples of a surgical therapy include, but are not limited to, acurative surgery (e.g., tumor removal surgery), a preventive surgery, alaparoscopic surgery, and a laser surgery.

Examples of the chemotherapeutic agents include, but are not limited to,Carboplatin or Cisplatin, Docetaxel, Gemcitabine, Nab-Paclitaxel,Paclitaxel, Pemetrexed, and Vinorelbine. Additional examples ofchemotherapy include, but are not limited to, Platinating agents, suchas Carboplatin, Oxaliplatin, Cisplatin, Nedaplatin, Satraplatin,Lobaplatin, Triplatin, Tetranitrate, Picoplatin, Prolindac, Aroplatinand other derivatives; Topoisomerase I inhibitors, such as Camptothecin,Topotecan, irinotecan/SN38, rubitecan, Belotecan, and other derivatives;Topoisomerase II inhibitors, such as Etoposide (VP-16), Daunorubicin, adoxorubicin agent (e.g., doxorubicin, doxorubicin hydrochloride,doxorubicin analogs, or doxorubicin and salts or analogs thereof inliposomes), Mitoxantrone, Aclarubicin, Epirubicin, Idarubicin,Amrubicin, Amsacrine, Pirarubicin, Valrubicin, Zorubicin, Teniposide andother derivatives; Antimetabolites, such as Folic family (Methotrexate,Pemetrexed, Raltitrexed, Aminopterin, and relatives or derivativesthereof); Purine antagonists (Thioguanine, Fludarabine, Cladribine,6-Mercaptopurine, Pentostatin, clofarabine, and relatives or derivativesthereof) and Pyrimidine antagonists (Cytarabine, Floxuridine,Azacitidine, Tegafur, Carmofur, Capacitabine, Gemcitabine, hydroxyurea,5-Fluorouracil (5FU), and relatives or derivatives thereof); Alkylatingagents, such as Nitrogen mustards (e.g., Cyclophosphamide, Melphalan,Chlorambucil, mechlorethamine, Ifosfamide, mechlorethamine,Trofosfamide, Prednimustine, Bendamustine, Uramustine, Estramustine, andrelatives or derivatives thereof); nitrosoureas (e.g., Carmustine,Lomustine, Semustine, Fotemustine, Nimustine, Ranimustine, Streptozocin,and relatives or derivatives thereof); Triazenes (e.g., Dacarbazine,Altretamine, Temozolomide, and relatives or derivatives thereof); Alkylsulphonates (e.g., Busulfan, Mannosulfan, Treosulfan, and relatives orderivatives thereof); Procarbazine; Mitobronitol, and Aziridines (e.g.,Carboquone, Triaziquone, ThioTEPA, triethylenemalamine, and relatives orderivatives thereof); Antibiotics, such as Hydroxyurea, Anthracyclines(e.g., doxorubicin agent, daunorubicin, epirubicin and relatives orderivatives thereof); Anthracenediones (e.g., Mitoxantrone and relativesor derivatives thereof); Streptomyces family antibiotics (e.g.,Bleomycin, Mitomycin C, Actinomycin, and Plicamycin); and ultravioletlight.

Chimeric Antigen Receptor (CAR) Therapy

Aspects of the disclosure relate to the recognition that the TME type ofa subject having (or suspected or at risk of having) cancer may beindicative of the likelihood that the subject will respond positively toCAR T-cell therapy.

Generally, a CAR is designed for a T-cell and is a chimera of asignaling domain of the T-cell receptor (TcR) complex and anantigen-recognizing domain (e.g., a single chain fragment (scFv) of anantibody) (Enblad et al., Human Gene Therapy. 2015; 26(8):498-505).

In some embodiments, an antigen binding receptor is a chimeric antigenreceptor (CAR). A T cell that expressed a CAR is referred to as a “CAR Tcell.” A CAR T cell receptor, in some embodiments, comprises a signalingdomain of the T-cell receptor (TcR) complex and an antigen-recognizingdomain (e.g., a single chain fragment (scFv) of an antibody) (Enblad etal., Human Gene Therapy. 2015; 26(8):498-505).

There are four generations of CARs, each of which contains differentcomponents. First generation CARs join an antibody-derived scFv to theCD3zeta (ζ or z) intracellular signaling domain of the T-cell receptorthrough hinge and transmembrane domains. Second generation CARsincorporate an additional domain, e.g., CD28, 4-1BB (41BB), or ICOS, tosupply a costimulatory signal. Third-generation CARs contain twocostimulatory domains fused with the TcR CD3-ζ chain. Third-generationcostimulatory domains may include, e.g., a combination of CD3z, CD27,CD28, 4-1BB, ICOS, or OX40. CARs, in some embodiments, contain anectodomain (e.g., CD3ζ), commonly derived from a single chain variablefragment (scFv), a hinge, a transmembrane domain, and an endodomain withone (first generation), two (second generation), or three (thirdgeneration) signaling domains derived from CD3Z and/or costimulatorymolecules (Maude et al., Blood. 2015; 125(26):4017-4023; Kakarla andGottschalk, Cancer J. 2014; 20(2):151-155).

In some embodiments, the chimeric antigen receptor (CAR) is a T-cellredirected for universal cytokine killing (TRUCK), also known as afourth generation CAR. TRUCKs are CAR-redirected T-cells used asvehicles to produce and release a transgenic cytokine that accumulatesin the targeted tissue, e.g., a targeted tumor tissue. The transgeniccytokine is released upon CAR engagement of the target. TRUCK cells maydeposit a variety of therapeutic cytokines in the target. This mayresult in therapeutic concentrations at the targeted site and avoidsystemic toxicity.

CARs typically differ in their functional properties. The CD3 signalingdomain of the T-cell receptor, when engaged, will activate and induceproliferation of T-cells but can lead to anergy (a lack of reaction bythe body's defense mechanisms, resulting in direct induction ofperipheral lymphocyte tolerance). Lymphocytes are considered anergicwhen they fail to respond to a specific antigen. The addition of acostimulatory domain in second-generation CARs improved replicativecapacity and persistence of modified T-cells. Similar antitumor effectsare observed in vitro with CD28 or 4-1BB CARs, but preclinical in vivostudies suggest that 4-1BB CARs may produce superior proliferationand/or persistence. Clinical trials suggest that both of thesesecond-generation CARs are capable of inducing substantial T-cellproliferation in vivo, but CARs containing the 4-1BB costimulatorydomain appear to persist longer. Third generation CARs combine multiplesignaling domains (costimulatory) to augment potency. Fourth generationCARs are additionally modified with a constitutive or inducibleexpression cassette for a transgenic cytokine, which is released by theCAR T-cell to modulate the T-cell response. See, for example, Enblad etal., Human Gene Therapy. 2015; 26(8):498-505; Chmielewski and Hinrich,Expert Opinion on Biological Therapy. 2015; 15(8): 1145-1154.

In some embodiments, a chimeric antigen receptor is a first-generationCAR. In some embodiments, a chimeric antigen receptor is asecond-generation CAR. In some embodiments, a chimeric antigen receptoris a third generation CAR. In some embodiments, the chimeric antigenreceptor is a fourth generation CAR, or a T-cell redirected foruniversal cytokine killing (TRUCK).

In some embodiments, a chimeric antigen receptor (CAR) comprises anextracellular domain comprising an antigen binding domain, atransmembrane domain, and a cytoplasmic domain. In some embodiments, aCAR is fully human. In some embodiments, the antigen binding domain of aCAR is specific for one or more antigens. Examples of antigen bindingdomain targets (e.g., antigens) include but are not limited tomesothelin, EGFRvIII, TSHR, CD19, CD123, CD22, CD20, CD30, CD171, CS-1,CLL-1, CD33, GD2, GD3, BCMA, Tn Ag, prostate specific membrane antigen(PSMA), ROR1, FLT3, FAP, TAG72, CD38, CD44v6, CEA, EPCAM, B7H3, KIT,IL-13Ra2, interleukin-11 receptor a (IL-11Ra), PSCA, PRSS21, VEGFR2,LewisY, CD24, platelet-derived growth factor receptor-beta (PDGFR-beta),SSEA-4, Folate receptor alpha (FRa), ERBB2 (Her2/neu), MUC1, epidermalgrowth factor receptor (EGFR), NCAM, Prostase, PAP, ELF2M, Ephrin B2,IGF-I receptor, CAIX, LMP2, gp100, bcr-abl, tyrosinase, EphA2, FucosylGM1, sLe, GM3, TGS5, HMWMAA, o-acetyl-GD2, Folate receptor beta,TEM1/CD248, TEM7R, CLDN6, GPRC5D, CXORF61, CD97, CD179a, ALK, Polysialicacid, PLAC1, GloboH, NY-BR-1, UPK2, HAVCR1, ADRB3, PANX3, GPR20, LY6K,OR51E2, TARP, WT1, NY-ESO-1, LAGE-1a, MAGE-A1, legumain, HPV E6, E7,MAGE A1, ETV6-AML, sperm protein 17, XAGE1, Tie 2, MAD-CT-1, MAD-CT-2,Fos-related antigen 1, p53, p53 mutant, prostein, survivin andtelomerase, PCTA-1/Galectin 8, MelanA/MART1, Ras mutant, hTERT, sarcomatranslocation breakpoints, ML-IAP, ERG (TMPRSS2 ETS fusion gene), NA17,PAX3, Androgen receptor, Cyclin B 1, MYCN, RhoC, TRP-2, CYP1B 1, BORIS,SART3, PAX5, OY-TES1, LCK, AKAP-4, SSX2, RAGE-1, human telomerasereverse transcriptase, RU1, RU2, intestinal carboxyl esterase, muthsp70-2, CD79a, CD79b, CD72, LAIR1, FCAR, LILRA2, CD300LF, CLEC12A,BST2, EMR2, LY75, GPC3, FCRL5, and IGLL1. In some embodiments, CAR isspecific for an epithelial cancer cell-specific antigen (e.g.,mesothelin, EGFRvII, PSMA, ROR1, FLT3, FAP, etc. In some embodiments, aCAR is specific for a lymphoma cancer cell-specific antigen (e.g., CD19,CD20, BCMA, etc.). In some embodiments, a CAR of the disclosurecomprises an antigen binding domain, such as a single chain FIT (scFv)specific for a tumor antigen. The choice of binding domain depends uponthe type and number of ligands that define the surface of a target cell.For example, the antigen binding domain may be chosen to recognize aligand that acts as a cell surface marker on target cells associatedwith a particular disease state, such as cancer or an autoimmunedisease. Thus, examples of cell surface markers that may act as ligandsfor the antigen binding domain in the CAR of the present disclosureinclude those associated with cancer cells and/or other forms ofdiseased cells. In some embodiments, a CAR is engineered to target atumor antigen of interest by way of engineering a desired antigenbinding domain that specifically binds to an antigen on a tumor cellencoded by an engineered nucleic acid, as provided herein.

An antigen binding domain (e.g., an scFv) that “specifically binds” to atarget or an epitope is a term understood in the art, and methods todetermine such specific binding are also known in the art. A molecule issaid to exhibit “specific binding” if it reacts or associates morefrequently, more rapidly, with greater duration and/or with greateraffinity with a particular target antigen than it does with alternativetargets. An antigen binding domain (e.g., an scFv) that specificallybinds to a first target antigen may or may not specifically bind to asecond target antigen. As such, “specific binding” does not necessarilyrequire (although it can include) exclusive binding.

In some embodiments, immune cells expressing a CAR are geneticallymodified to recognize multiple targets or antigens, which permits therecognition of unique target or antigen expression patterns on tumorcells. Examples of CARs that can bind multiple targets include: “splitsignal CARs,” which limit complete immune cell activation to tumorsexpressing multiple antigens; “tandem CARs” (TanCARs), which containectodomains having two scFvs; and “universal ectodomain CARs,” whichincorporate avidin or a fluorescein isothiocyanate (FITC)-specific scFvto recognize tumor cells that have been incubated with tagged monoclonalantibodies (mAbs).

A CAR is considered “bispecific” if it recognizes two distinct antigens(has two distinct antigen recognition domains). In some embodiments, abispecific CAR is comprised of two distinct antigen recognition domainspresent in tandem on a single transgenic receptor (referred to as aTanCAR; see, e.g., Grada Z et al. Molecular Therapy Nucleic Acids 2013;2:e105, incorporated herein by reference). Thus, methods, in someembodiments, comprise delivering to a tumor an engineered nucleic acidthat encode an antigen, or delivering to a tumor an engineered nucleicacid that induces expression of a self-antigen, and delivering to thetumor an immune cell expressing a bispecific CAR that binds to twoantigens, one of which is encoded by the engineered nucleic acid.

In some embodiments, a CAR is an antigen-specific inhibitory CAR (iCAR),which may be used, for example, to avoid off-tumor toxicity (Fedorov, VD et al. Sci. Transl. Med. published online Dec. 11, 2013, incorporatedherein by reference). iCARs contain an antigen-specific inhibitoryreceptor, for example, to block nonspecific immunosuppression, which mayresult from extratumor target expression. iCARs may be based, forexample, on inhibitory molecules CTLA-4 or PD-1. In some embodiments,these iCARs block T cell responses from T cells activated by eithertheir endogenous T cell receptor or an activating CAR. In someembodiments, this inhibiting effect is temporary.

In some embodiments, a “spacer” domain or “hinge” domain is locatedbetween an extracellular domain (comprising the antigen binding domain)and a transmembrane domain of a CAR, or between a cytoplasmic domain anda transmembrane domain of the CAR. A “spacer domain” refers to anyoligopeptide or polypeptide that functions to link the transmembranedomain to the extracellular domain and/or the cytoplasmic domain in thepolypeptide chain. A “hinge domain” refers to any oligopeptide orpolypeptide that functions to provide flexibility to the CAR, or domainsthereof, or to prevent steric hindrance of the CAR, or domains thereof.In some embodiments, a spacer domain or hinge domain may comprise up to300 amino acids (e.g., 10 to 100 amino acids, or 5 to 20 amino acids).In some embodiments, one or more spacer domain(s) may be included inother regions of a CAR.

In some embodiments, a CAR comprises a transmembrane domain. Examples ofCAR transmembrane domains include but are not limited to CD28, CD3epsilon, CD45, CD4, CD5, CD8, CD9, CD16, CD22, CD33, CD37, CD64, CD80,CD86, CD134, CD137 and CD154.

In some embodiments, a CAR comprises an intracellular signaling domain.Examples of CAR intracellular signaling domains include but are notlimited to MHC class I molecule, a TNF receptor protein, anImmunoglobulin-like protein, a cytokine receptor, an integrin, asignaling lymphocytic activation molecule (SLAM protein), an activatingNK cell receptor, BTLA, a Toll ligand receptor, OX40, CD2, CD7, CD27,CD28, CD30, CD40, CDS, ICAM-1, LFA-1 (CD1 1a/CD18), 4-1BB (CD137),B7-H3, CDS, ICAM-1, ICOS (CD278), GITR, BAFFR, LIGHT, HVEM (LIGHTR),KIRDS2, SLAMF7, NKp80 (KLRF1), NKp44, NKp30, NKp46, CD19, CD4, CD8alpha,CD8beta, IL2R beta, IL2R gamma, IL7R alpha, ITGA4, VLA1, CD49a, ITGA4,IA4, CD49D, ITGA6, VLA-6, CD49f, ITGAD, CD11d, ITGAE, CD103, ITGAL, CD11a, LFA-1, ITGAM, CD1 1b, ITGAX, CD1 1c, ITGB 1, CD29, ITGB2, CD18,LFA-1, ITGB7, NKG2D, NKG2C, TNFR2, TRANCE/RANKL, DNAM1 (CD226), SLAMF4(CD244, 2B4), CD84, CD96 (Tactile), CEACAM1, CRT AM, Ly9 (CD229), CD160(BY55), PSGL1, CD100 (SEMA4D), CD69, SLAMF6 (NTB-A, Ly108), SLAM(SLAMF1, CD150, IPO-3), BLAME (SLAMF8), SELPLG (CD162), LTBR, LAT, GADS,SLP-76, PAG/Cbp, CD19, and CD3ζ, Fc receptor gamma signaling domain.

In some embodiments, as an example of the disclosure disclosed herein,CARs may be used in adoptive cell transfer, wherein immune cells areremoved from a subject and modified so that they express receptorsspecific to an antigen, e.g., a tumor-specific antigen. The modifiedimmune cells, which may then recognize and kill the cancer cells, arereintroduced into the subject (Pule, et al., Cytotherapy. 2003; 5(3):211-226; Maude et al., Blood. 2015; 125(26): 4017-4023, each of which isincorporated herein by reference). In some embodiments, a CAR isexpressed by a T-cell. In some embodiments, a CAR is expressed by aregulatory T-cell (e.g., a CAR T-reg).

As disclosed herein, in some embodiments, the adoptive cell transfertherapy is a CAR-T cell therapy. In some embodiments, the CAR-T celltherapy described in this application is administered at a dose of about0.2×10⁶, about 0.3×10⁶, about 0.4×10⁶, about 0.5×10⁶, about 0.6×10⁶,about 0.7×10⁶, about 0.8×10⁶, about 0.9×10⁶, about 1×10⁶, about 2×10⁶,about 3×10⁶, about 4×10⁶, about 5×10⁶, about 6×10⁶, about 7×10⁶, about8×10⁶, about 9×10⁶, about 10×10⁶, about 11×10⁶, about 12×10⁶, about13×10⁶, about 14×10⁶, about 15×10⁶ CAR-positive viable T cells per Kgbody weight, inclusive of all ranges and subranges therebetween, to asubject in need thereof.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at a dose of about 0.2×10⁶, about 0.3×10⁶,about 0.4×10⁶, about 0.5×10⁶, about 0.6×10⁶, about 0.7×10⁶, about0.8×10⁶, about 0.9×10⁶, about 1×10⁶, about 2×10⁶, about 3×10⁶, about4×10⁶, about 5×10⁶, CAR-positive viable T cells per Kg body weight,inclusive of all ranges and subranges therebetween, to a child or to ayoung adult who is up to 25 years old.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at a dose of about 1×10⁷, about 2×10⁷, about3×10⁷, about 4×10⁷, about 5×10⁷, CAR-positive viable T cells per Kg bodyweight, inclusive of all ranges and subranges therebetween, to a subjectin need thereof. In some embodiments, the CAR-T cell therapy describedin this application is administered at a dose of about 0.6×10⁸, about0.7×10⁸, about 0.8×10⁸, about 0.9×10⁸, about 1×10⁸, about 2×10⁸, about3×10⁸, about 4×10⁸, about 5×10⁸, about 6×10⁸, CAR-positive viable Tcells per Kg body weight, inclusive of all ranges and subrangestherebetween, to a subject in need thereof. In some embodiments, thesubject in need thereof is an adult who is more than 25 years old.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at a dose of about 1×10⁹, about 2×10⁹, about3×10⁹, about 4×10⁹, about 5×10⁹, CAR-positive viable T cells per Kg bodyweight, inclusive of all ranges and subranges therebetween, to a subjectin need thereof. In some embodiments, the CAR-T cell therapy describedin this application is administered at a dose of about 1×10¹⁰, about2×10¹⁰, about 3×10¹⁰, CAR-positive viable T cells per Kg body weight,inclusive of all ranges and subranges therebetween, to a subject in needthereof.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at one dose, two doses, three doses, fourdoses, five doses, six doses, seven doses, eight doses, nine doses, tendoses, to a subject in need thereof. In some embodiments, the CAR-T celltherapy described in this application is administered at any doses to asubject in need thereof according to the instructions by healthprofessionals.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at a dose of about 50×10⁶, about 51×10⁶,about 52×10⁶, about 53×10⁶, about 54×10⁶, about 55×10⁶, about 56×10⁶,about 57×10⁶, about 58×10⁶, about 59×10⁶, about 60×10⁶, about 61×10⁶,about 62×10⁶, about 63×10⁶, about 64×10⁶, about 65×10⁶, about 66×10⁶,about 67×10⁶, about 68×10⁶, about 69×10⁶, about 70×10⁶, about 71×10⁶,about 72×10⁶, about 73×10⁶, about 74×10⁶, about 75×10⁶, about 76×10⁶,about 77×10⁶, about 78×10⁶, about 79×10⁶, about 80×10⁶, about 81×10⁶,about 82×10⁶, about 83×10⁶, about 84×10⁶, about 85×10⁶, about 86×10⁶,about 87×10⁶, about 88×10⁶, about 89×10⁶, about 90×10⁶, about 91×10⁶,about 92×10⁶, about 93×10⁶, about 94×10⁶, about 95×10⁶, about 96×10⁶,about 97×10⁶, about 98×10⁶, about 99×10⁶, about 100×10⁶, about 101×10⁶,about 102×10⁶, about 103×10⁶, about 104×10⁶, about 105×10⁶, about106×10⁶, about 107×10⁶, about 108×10⁶, about 109×10⁶, about 110×10⁶,CAR-positive viable T cells, inclusive of all ranges and subrangestherebetween, to a subject in need thereof.

In some embodiments, the CAR-T cell therapy described in thisapplication is administered at a dose of about 300×10⁶, about 301×10⁶,about 302×10⁶, about 303×10⁶, about 304×10⁶, about 305×10⁶, about306×10⁶, about 307×10⁶, about 308×10⁶, about 309×10⁶, about 310×10⁶,about 311×10⁶, about 312×10⁶, about 313×10⁶, about 314×10⁶, about315×10⁶, about 316×10⁶, about 317×10⁶, about 318×10⁶, about 319×10⁶,about 320×10⁶, about 321×10⁶, about 322×10⁶, about 323×10⁶, about324×10⁶, about 325×10⁶, about 326×10⁶, about 327×10⁶, about 328×10⁶,about 329×10⁶, about 330×10⁶, about 331×10⁶, about 332×10⁶, about333×10⁶, about 334×10⁶, about 335×10⁶, about 336×10⁶, about 337×10⁶,about 338×10⁶, about 339×10⁶, about 340×10⁶, about 341×10⁶, about342×10⁶, about 343×10⁶, about 344×10⁶, about 345×10⁶, about 346×10⁶,about 347×10⁶, about 348×10⁶, about 349×10⁶, about 350×10⁶, about351×10⁶, about 352×10⁶, about 353×10⁶, about 354×10⁶, about 355×10⁶,about 356×10⁶, about 357×10⁶, about 358×10⁶, about 359×10⁶, about360×10⁶, about 361×10⁶, about 362×10⁶, about 363×10⁶, about 364×10⁶,about 365×10⁶, about 366×10⁶, about 367×10⁶, about 368×10⁶, about369×10⁶, about 370×10⁶, about 371×10⁶, about 372×10⁶, about 373×10⁶,about 374×10⁶, about 375×10⁶, about 376×10⁶, about 377×10⁶, about378×10⁶, about 379×10⁶, about 380×10⁶, about 381×10⁶, about 382×10⁶,about 383×10⁶, about 384×10⁶, about 385×10⁶, about 386×10⁶, about387×10⁶, about 388×10⁶, about 389×10⁶, about 390×10⁶, about 391×10⁶,about 392×10⁶, about 393×10⁶, about 394×10⁶, about 395×10⁶, about396×10⁶, about 397×10⁶, about 398×10⁶, about 399×10⁶, about 400×10⁶,about 401×10⁶, about 402×10⁶, about 403×10⁶, about 404×10⁶, about405×10⁶, about 406×10⁶, about 407×10⁶, about 408×10⁶, about 409×10⁶,about 410×10⁶, about 411×10⁶, about 412×10⁶, about 413×10⁶, about414×10⁶, about 415×10⁶, about 416×10⁶, about 417×10⁶, about 418×10⁶,about 419×10⁶, about 420×10⁶, about 421×10⁶, about 422×10⁶, about423×10⁶, about 424×10⁶, about 425×10⁶, about 426×10⁶, about 427×10⁶,about 428×10⁶, about 429×10⁶, about 430×10⁶, about 431×10⁶, about432×10⁶, about 433×10⁶, about 434×10⁶, about 435×10⁶, about 436×10⁶,about 437×10⁶, about 438×10⁶, about 439×10⁶, about 440×10⁶, about441×10⁶, about 442×10⁶, about 443×10⁶, about 444×10⁶, about 445×10⁶,about 446×10⁶, about 447×10⁶, about 448×10⁶, about 449×10⁶, about450×10⁶, about 451×10⁶, about 452×10⁶, about 453×10⁶, about 454×10⁶,about 455×10⁶, about 456×10⁶, about 457×10⁶, about 458×10⁶, about459×10⁶, about 460×10⁶, CAR-positive viable T cells, inclusive of allranges and subranges therebetween, to a subject in need thereof.

In some embodiments, the administration of the adoptive cell transfertherapy to a subject in need thereof is intravenous. In someembodiments, the administration of the adoptive cell transfer therapy toa subject in need thereof is intramuscular. In some embodiments, theadministration of the adoptive cell transfer therapy to a subject inneed thereof is any route that is suitable for the therapy.

In some embodiments, the CAR-T cell therapy described in thisapplication is BREYANZI® (lisocabtagene maraleucel). In someembodiments, the CAR-T cell therapy described in this application isTECARTUS™ (brexucabtagene autoleucel). In some embodiments, the CAR-Tcell therapy described in this application is KYMRIAH™(tisagenlecleucel). In some embodiments, the CAR-T cell therapydescribed in this application is YESCARTA™ (axicabtagene ciloleucel). Insome embodiments, the CAR-T cell therapy described in this applicationis ABECMA® (idecabtagene vicleucel). In some embodiments, the CAR-T celltherapy described in this application can be any therapy that issuitable as understood by a skilled person in the art.

In some embodiments, the CAR-T cell therapy described in thisapplication is AUTO3 (CD19/22 CAR T cells). In some embodiments, theCAR-T cell therapy described in this application is CART-19. In someembodiments, the CAR-T cell therapy described in this application isanti-B cell maturation antigen (BCMA) CAR T cells. In some embodiments,the CAR-T cell therapy described in this application is Epidermal growthfactor receptor (EGFRv)III Chimeric antigen receptor (CAR) transducedPBL.

In some embodiments, a subject having a TME type that is not expected torespond to a CAR T-cell therapy (e.g., a CAR T-cell monotherapy) istreated with a combination of a CAR T-cell and one or more additionaltherapeutic agents. In some embodiments, the one or more additionaltherapeutic agents are expressed by the CAR-T cell. In some embodiments,the one or more additional therapeutic agents are administeredseparately from the CAR T-cell therapy. The one or more additionaltherapeutic agents may be delivered before, simultaneously (e.g., at thesame time, for example co-administered) with, or after the CAR T-celltherapy. In some embodiments, the one or more additional therapeuticagents are each selected from Utomilumab (e.g., CD137 activators),Rituximab+Lenalidomide, Tazemetostat (e.g., EZH2 inhibitors), immunecheckpoint inhibitors (e.g., PD-1 inhibitors, PD-L1 inhibitors, etc.),Selinexor (e.g., XPO1 inhibitors), TLR agonists (e.g., TLR 1, 2, 7, 9agonists), Venetoclax (e.g., BCL2 inhibitors), Azacitidine, Ibrutinib,antiangiogenic agents, TGFBR2 inhibitors, WNT inhibitors, cytokinetherapy, and personalized cancer vaccines.

EXAMPLES Example 1 Association of CAR-T Efficacy in Dependence on TMETypes in Solid Tumor Cancer

This example describes identification of blood cancer and lymphoma orsolid tumor cancer tumor microenvironment (TME) types based uponmolecular function profiling of cells from biological samples (e.g.,solid tumor cells and hematological cancer cells) obtained from cancerpatients. FIG. 2 depicts representative data identifying four tumormicroenvironment types (A, B, C, and D) from patients having lymphoma.The identification of TME types is useful, in some embodiments, fordetermining whether or not a patient is likely to respond positively tocertain adoptive cell therapies, for example CAR T-cell therapies orcombination therapies that include CAR T-cell therapies. Briefly, bloodcancer and lymphoma TME types identified, and their expected response toCAR-T therapies, are described below in Table 1. Table 2 describes solidtumor cancer TME types and their expected response to CAR T-celltherapies.

The blood cancer and lymphoma type “A” is characterized by animmuno-suppressive TME. Many macrophages that suppress T-cell functionare present. There is also a high percentage of exhausted T-cells. Thus,type A patients are expected to be resistant to treatment with CART-cell therapies that are not resistant to T-cell exhaustion orsuppressive environments. CAR T-cell therapies that are resistant tohigh acidosis levels may also be effective. Combinations of CAR T-celltherapies with immune checkpoint inhibitors may be effective. However,type A also is characterized as having high levels of CD8+IL6 producingcells.

The blood cancer and lymphoma type “B” is characterized by havinggenotypes and/or phenotypes close to normal cells. Type B TME is alsocharacterized by an increased number of CD4+, Follicular helper T-cells(Tfh), and, in certain cancers, lymphatic endothelium. Generally, type Bhas a low tumor content and a high percentage of non-malignant B-cells.There is also a high percentage of HVEM, CD83, STATE, and/or FOXO1mutations. Cells often depend on the microenvironment (e.g., Tfh cells)and rarely on intrinsic pathways. Most of the tumors of type B areexpected to respond to Rituximab. Patients of this type are alsoexpected to respond to CAR-T therapy that targets cancer cell surfaceligands (e.g., if CD19 is expressed on the surface then a CAR T-celltherapy targeting CD19 is expected to provide a therapeutic benefit).The blood cancer and lymphoma type “C” is characterized by a TMEenriched with fibroblasts. Cancer cells in type C are highlyvascularized. The TME is characterized by low lymphocyte and macrophageinfiltration. Examples of cancers having type C TME include non-Hodgkinslymphomas, such as DLBCL, follicular lymphoma (FL), and mantle celllymphoma (MCL). In the TME, communication with T-cells is disrupted byB2M, CIITA Loss, EZH2 GOF; Cells in TME type C may also be characterizedby PDL1 amplifications, CD70, TNFRSF9 losses. Downstream NFkB signalingis highly active through mutations in CARD11, a20, BTK, NFKBIE, MALT1,and/or TRAF2. Migratory pathways are often disrupted (e.g., G-alphacomplex) by alterations in GNA13 and/or P2RY8. Type C comprises cellshaving a high mutation load, for example ST2 cancers or EZB typecancers. Type C TME cancers are expected to respond to immune checkpointinhibitors, as cells frequently express high levels of PD-L1. However,high levels of IL-6 produced by the type C microenvironment (especiallyby non-CARs, CD8+ T-cells and Macrophages) may be associated with severetoxicity. CAR T-cell therapies administered in combination with immunecheckpoint inhibitors are expected to be therapeutically effective.However, given the immunosuppressive TME of type C, CAR T-cellsadministered as a monotherapy are not expected to provide anytherapeutic benefit.

The blood cancer and lymphoma type “D” is characterized by an immunecell depleted TME having a low number of immune and stromal infiltratesand a CD4/CD8 bias towards CD8+ cells. Type D also is characterized ashaving a higher tumor content and higher percentage ofrelapsed/refractory cases than other types. Tumors in a type D TME aretypically hypermethylated, aneuploid or polyploid, with a high mutationload and circulating nucleic acid (CNA) load. In the context oflymphomas, type D has a high occurrence of double hit cancers, forexample DHITsig+ cases, as well as p16 double loss, and EZB typecancers. In the type D TME, PI3K is typically more active than NFkB anda large percentage of cells comprise anti-apoptotic genes amplifications(e.g., BAK), TMEM30A mutations (e.g., B cell receptor mutations), and ahigh TP53 loss rate. CAR T-cell therapy is not expected to have atherapeutic benefit for type D TME because certain tumors in this TMEare not dependent on B cell receptors, and NFkB intrinsically activatedtumors are not expected to respond to CAR T-cell therapy. However, dueto the depleted TME of type D, CAR T-cell therapy may be expected to beeffective in PI3K-dependent MYC-negative cancers. Additionally, CART-cell therapies may synergize with certain chemotherapies (e.g.,Ibrutinib and other BTK inhibitors) in a type D TME.

TABLE 1 CAR-T with TME types A-D in the context of Blood Cancer: CAR-Ttarget - refers to the target molecule on the surface of malignantcells, which is selected as target of CAR-T, for example CD19, CD20,etc. Although the table includes information specific to different typesof lymphoma, this example is applicable to other blood cancers, examplesof which are provided herein. Potential combinational therapy toovercome Response Response resistance or Main TME type Additional typeto 1-2 gen CAR-T to 3-4gen CAR-T increase efficacy Type-B CAR-T targetCould be treated Could be treated Utomilumab (CD137 (GCB or ABC)expressed with CAR-T with CAR-T activator) Rituximab + LenalidomideUmbralisib and other PI3K delta/gamma inhibitors Type-B CAR-T targetLikely not Tandem CAR/Dual — (GCB or ABC) not expressed responsiveCar/CAR Pooling Type-C CAR-T target Likely responsive “Armored” CARswith Checkpoint inhibitors? (GCB or ABC) expressed IL-18, IL-15, IL-12,IL-7 etc./CARs with checkpoint blockade antibodies Type-C CAR-T targetLikely not Tandem CAR/Dual — (GCB or ABC) not expressed responsiveCar/CAR Pooling Type-C EZB or A53 Likely responsive — Tazemetostat (GCBor ABC) or MYC+ (EZH2 inhibitor), venetoclax (BCL2 inhibitor) Type-ACAR-T target Likely not CARs with checkpoint Checkpoint inhibitors, (GCBor ABC) expressed responsive due to blockade antibodies/CAR-T TLR 1, 2,7, 9 agonists immune suppression Cells with EGFRt safety system(Immunomodulators) (+rituximab or cetuximab) Lenalidomide Checkpointinhibitors Type-A CAR-T target Likely not Tandem CAR/Dual Lenalidomide(GCB or ABC) not expressed responsive due to Car/CAR Pooling immunesuppression Type-A EZB or A53 Likely not — Tazemetostat (GCB or ABC) orMYC+ responsive (EZH2 inhibitor) Type-D GCB CAR-T target Likely notTandem CAR/Dual Venetoclax not expressed responsive Car/CAR Pooling(BCL2 inhibitors) Type-D GCB DHIT-/MYC CAR-T May respond — Venetoclaxtarget expressed (BCL2 inhibitors) Type-D GCB DHIT+/MYC+ May respond —Azacitidine, or EZB or A53 Tazemetostat Type-D ABC CAR-T target Mayrespond — Rituximab, Rituximab + expressed Lenalidomide Type-D ABC CAR-Ttarget Likely not Tandem CAR/Dual not expressed responsive Car/CARPooling Type-D ABC MCD, TMEM30A Likely responsive —//— Ibrutinib mutants(10.1038/ to CAR-T Synergism s41591-020-0757-z) with BKT inhibitorsmutants Type-D ABC DHIT+/MYC+ May respond Azacitidine, Selinexor, or EZBor A53 Venetoclax, Tazemetostat. Ibrutinib Utomilumab (CD137 activator)

TABLE 2 CAR-T with TME types A-D in the context of Solid Tumors (e.g.,melanoma): (CAR-T target - refers to a target molecule on the surface ofmalignant cells, which is selected as a target of CAR-T, for exampleMSLN, MAGEA3, CEA, EGFRvIII). Potential combinational therapy toovercome Response to 1-2 Response to 3-4 resistance or Main TME typeAdditional type gen CAR-T gen CAR-T increase efficacy Type A (ImmuneCAR-T target Unknown CAR-T cells with Antiangiogenic agents Enriched,fibrotic) expressed HPSE expression TGFBR2 inhibitors Type A (ImmuneCAR-T target Potentially Tandem CAR/Dual TGFBR2 inhibitors + Enriched,fibrotic) not expressed resistant Car/CAR Pooling Checkpoint inhibitorsType B (Immune CAR-T target Potentially CARs with checkpoint Checkpointinhibitors Enriched, non-fibrotic) expressed sensitive blockadeantibodies Type B (Immune CAR-T target Potentially Tandem CAR/DualEnriched, non-fibrotic) not expressed resistant Car/CAR Pooling Type C(Fibrotic) CAR-T target Potentially CAR-T Cells with IL-7 TGFBR2inhibitors expressed resistant and CCL19 Expression/CAR WNT inhibitors Tcells with a dominant- (to restrain fibrosis) negative TGF-βRII(dnTGF-βRII) expression/CAR-T cells with HPSE expression Type C(Fibrotic) CAR-T target Potentially Tandem CAR/Dual — not expressedresistant Car/CAR Pooling Type D (Immune depleted, CAR-T targetPotentially “Armored” CARs Cytokine therapy non-fibrotic, malignant)expressed sensitive with IL-18, IL-15, (IL2, IFNa) IL-12, IL-7 etc.Personalized Vaccination Type D (Immune depleted, CAR-T targetPotentially Tandem CAR/Dual — non-fibrotic, malignant) not expressedresistant Car/CAR Pooling

Example 2

This Example describes methods and algorithms for identification oflymphoma microenvironment (LME) types within Diffuse Large B-CellLymphoma (DLBCL) patients, and prognostic stratification of thosepatients (e.g., overall survival (OS), progression-free survival at 24months (PFS24), etc.) based, at least in part, upon the LME type of thesubject.

A large number of public DLBCL datasets (e.g., expression data, RNA-seqdata, whole exome sequencing data, etc.) was collected. Roughly half ofthe samples in the data set have overall survival (OS) andprogression-free survival (PFS) annotations and are derived from avariety of different sources. Data sets were obtained from the followingpublicly-available cohorts ‘NCICGCI’, ‘NCICCR’, ‘GSE22898’, ‘Dave_BL’,‘ICGC_MALY_DE’, ‘Regensburg’, ‘BAGS’, ‘GSE64555’, ‘GSE68895’,‘GSE69049’, ‘GSE69051’, ‘GSE87371’, ‘GSE93984’, ‘GSE11318’, ‘GSE10846’,‘GSE12195’, ‘GSE117556’, ‘GSE19246’, ‘GSE23501’, ‘GSE31312’, ‘GSE32918’,‘E-TABM-346’, ‘GSE98588’, and ‘GSE38202’, ‘GSE34171_1’. A total of 4448samples (2447/2001 GCB/ABC) were analyzed. Among them, 1702 patientswith known PFS data (1143/559) were analyzed.

A lymphoma microenvironment (LME) type was determined for each subjectbased upon gene expression signatures, as described below.

In some embodiments, gene expression signatures (e.g., a signaturecomprising a plurality of gene group expression scores) representing themicroenvironment of a DLBCL sample are calculated by single sample geneset enrichment analysis (ssGSEA) of one or more genes in one or more ofthe gene sets shown in Table 3. Methods of performing gene setenrichment analysis are known, for example as described by:www.genepattern.org/modules/docs/ssGSEAProjection/4#:˜:text=Single%2Dsample%20GSEA %20(ssGSEA),down %2Dregulated%20within%20a%20sample;Subramanian et al. Gene set enrichment analysis: A knowledge-basedapproach for interpreting genome-wide expression profiles. PNAS. 2005;102(43):15545-15550; and Barbie D A et al. Systematic RNA interferencereveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462:108-112, the entire contents of each of which are incorporatedherein by reference.

In some embodiments, one or more gene expression signatures arecalculated using methods described by US Patent Publication No.2020-0273543, entitled “SYSTEMS AND METHODS FOR GENERATING, VISUALIZINGAND CLASSIFYING MOLECULAR FUNCTIONAL PROFILES”, the entire contents ofwhich are incorporated herein by reference.

TABLE 3 Gene Group Gene Group Genes Lymphatic JAM3, PPP1R13B, CXCL12,PDPN, endothelium (LEC) CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1,SOX18, JAM2 Angiogenesis (VEC) CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF,CXCR2, ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, ANGPT2 Cancer-associatedCOL1A1, MMP2, LGALS1, MMP7, LRP1, fibroblasts(CAF) CD248, S100A4, FAP,FGF2, MMP9, CTGF, ACTA2, FN1, COL1A2, COL5A1, COL6A1, MMP3, CA9, PRELP,FBLN1, COL6A3, COL11A1, TGFB3, MMP12, MFAP5, MMP1, COL6A2, TIMP1,COL4A1, TGFB1, LUM, LGALS9, PTGS2, TGFB2 Fibroblastic reticular PDGFRA,ACTA2, ICAM1, NT5E, VIM, cells (FRC) PDPN, THY1, DES, VCAM1, PTGS2, LTBRMatrix (ECM) COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, COL4A1 MatrixRemodeling TIMP1, TIMP2, MMP2, MMP9, CA9 (ECM remodeling) Granulocytetraffic KITLG, , CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1,CXCL2 Protumor cytokines CCL4, IL6, TNFSF13B, MIF, (IS cytokines) CXCL8,IL22, IL10 Follicular Dendritic PDPN, TNFRSF1A, LTBR, FDCSP, CLU, Cells(FDC) PRNP, BST1 Macrophages IL10, MSR1, ARG1, CSF1R, CD163, MRC1, CSF1M1 signature TNF, NOS2, IL1B, CMKLR1, (activated M1) Effector cellCXCL11, CXCL10, CXCL9, CXCR3, traffic (T cell traffic) CX3CL1, CCL5,CX3CR1 Major histocompatibility HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-complex II (MHC-II) DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, HLA-DMB Majorhistocompatibility TAP1, HLA-C, B2M, HLA-B, HLA-A, TAP2 complex I(MHC-I) Follicular B helper CD40LG, SH2D1A, CD84, CXCR5, IL4, T cells(TFH) IL6, MAF, BCL6, IL21, ICOS Regulatory T cells (Treg) CCR8, CTLA4,IKZF2, IKZF4, FOXP3, IL10, TNFRSF18 T cells (TIL) CD3D, TRAT1, TBX21,TRBC2, ITK, CD28, CD3E, TRBC1, TRAC, CD3G Checkpoint inhibition CTLA4,HAVCR2, CD274, PDCD1, BTLA, (IS checkpoints) TIGIT, PDCD1LG2, LAG3Natural Killer Cells SH2D1B, GZMH, GZMB, CD160, (NK cells) KLRK1, NCR3,CD244, IFNG, GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4,KLRF1 B cell traffic CXCL13, CXCR5, CCR6, CCL20 Benign B cells (B cells)CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, FCRL5 Tumor proliferation rate MCM6, AURKB, ESCO2,CCNB1, AURKA, (cell proliferation) MKI67, CCND1, CCNE1, MCM2, MYBL2,E2F1, CETN3, CDK2, PLK1, BUB1 Nuclear factor PROGENY pathway score kappaB (NFkB) Phosphoinositide 3- PROGENY pathway score kinase (PI3K) p53PROGENY pathway score

After determining the gene expression signatures each sample,unsupervised clustering was performed using Leiden algorithm. Four DLBCLLME types were identified based on the clusters. Examples of LME typesare described for example by Cerchietti et al. Blood (2019) 134(Supplement_1): 656, the entire contents of which are incorporatedherein by reference:

LME-1 DLBCL is characterized by an “immunosuppressive” microenvironmentenriched for T regulatory cells, myeloid-derived suppressor cells,CD8^(PD1high) natural killer and macrophages type 2, and prevalence ofgenetic mechanisms of immune escape in malignant cells such as mutationsin B2M and CD70. Malignant cells in LME-1 DLBCL present high activity ofNF-kB and JAK/STAT signaling pathways, likely due to high frequency ofco-occurring MYD88^(L265) and CD79B mutations and the presence of acytokine rich milieu including high expression of IL10, IL6 and TNFS13B.

LME-2 DLBCL is characterized by an “anti-tumor immunity”microenvironment enriched for T cells, follicular T_(H) and folliculardendritic cells (FDC), and present the highest number of BCL2translocations and EZH2 mutations and activation of cell motility andchemotaxis pathways relative to other LME types. Lymphoma cells expresshigher levels of CCL20, CCR6 and CXCR5.

LME-3 DLBCL is characterized by a “mesenchymal” microenvironmentenriched for cancer-associated fibroblasts (CAFs), reticular dendriticcells (DC), FDC, and endothelial cells. Lymphoma cells show highermutations in BCR/Pi3K signaling intermediates SGK1 and GNA13 andactivation of the TGFB signaling and matrix remodeling pathways. LME-3DLBCLs express higher levels of MMP9, MMP2, TIMP1 and TIMP2 than otherLME types. LME-3 DLBCL also has a higher proportion of non-cellular LMEcomponent represented by the extracellular matrix (ECM).

LME-4 DLBCL is characterized by a “depleted” microenvironment with anincreased proportion of lymphoma cells with mutations in MYD88, PIM1 andHLA-C, and higher genomic instability and epigenetic heterogeneity(e.g., by DNA methylation). Lymphoma cells show activation of Pi3Ksignaling and hypermethylation and low expression of the TGFB mediatorSMAD1.

LME types were observed to be associated with OS and progression-freesurvival at 24 months (PFS24) for each LME type, for each cancel cell oforigin (COO) separately. FIG. 3 shows representative data indicatingthat Lymphoma Microenvironment (LME) types correlate with overallsurvival (OS), independent of cancer cell of origin (COO), according tocertain aspects of the invention. Left panel shows a Kaplan-Meier (KM)survival plot for a sample of 1010 patients having Activated B cell(ABC) lymphoma. Right panel shows a KM survival plot for a sample of1456 patients having Germinal center B cell-like (GCB) lymphoma. FIG. 4shows representative data indicating that Lymphoma Microenvironment(LME) types correlate with progression-free survival (PFS), independentof cancer cell of origin (COO), according to certain aspects of theinvention. Left panel shows a Kaplan-Meier (KM) survival plot for acohort of 839 patients having Activated B cell (ABC) lymphoma. Rightpanel shows a KM survival plot for a cohort of 1194 patients havingGerminal center B cell-like (GCB) lymphoma. FIG. 5 shows representativedata demonstrating stratification of progression-free survival at 24months (PFS24) according to COO and TME type, according to certainaspects of the invention. The left panel shows stratification ofsubjects having ABC and the right panel shows stratification of subjectshaving GCB.

Next, DLBCL samples were typed using LME in combination with COO andInternational Prognostic Index (IPI) score. Methods of calculating IPIscores are known, for example as described by “InternationalNon-Hodgkins Lymphoma Prognostic Factors Project. A predictive model foraggressive non-Hodgkins lymphoma.” N Engl J Med. 1993; 329(14):987-994.FIG. 6 shows representative data demonstrating stratification ofprogression-free survival at 24 months (PFS24) according to COO, TMEtype, and International Prognostic Index (IPI) score, according tocertain aspects of the invention. Data indicate poor prognosis forgroups “ABC IPI-High” and (not LME-C, e.g., LME-A, LME-B, or LME-D) or“GCB IPI-High” LME4; ABC IPI-Intermediate LME3/4 subject also havenon-favorable PFS24.

EQUIVALENTS AND SCOPE

The terms “program” or “software” are used herein in a generic sense torefer to any type of computer code or set of processor-executableinstructions that can be employed to program a computer or otherprocessor (physical or virtual) to implement various aspects ofembodiments as discussed above. Additionally, according to one aspect,one or more computer programs that when executed perform methods of thetechnology described herein need not reside on a single computer orprocessor, but may be distributed in a modular fashion among differentcomputers or processors to implement various aspects of the technologydescribed herein.

Processor-executable instructions may be in many forms, such as programmodules, executed by one or more computers or other devices. Generally,program modules include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Typically, the functionality of the program modulesmay be combined or distributed.

Also, data structures may be stored in one or more non-transitorycomputer-readable storage media in any suitable form. For simplicity ofillustration, data structures may be shown to have fields that arerelated through location in the data structure. Such relationships maylikewise be achieved by assigning storage for the fields with locationsin a non-transitory computer-readable medium that convey relationshipbetween the fields. However, any suitable mechanism may be used toestablish relationships among information in fields of a data structure,including through the use of pointers, tags or other mechanisms thatestablish relationships among data elements.

Various inventive concepts may be embodied as one or more processes, ofwhich examples have been provided. The acts performed as part of eachprocess may be ordered in any suitable way. Thus, embodiments may beconstructed in which acts are performed in an order different thanillustrated, which may include performing some acts simultaneously, eventhough shown as sequential acts in illustrative embodiments.

As used herein in the specification and in the claims, the phrase “atleast one,” in reference to a list of one or more elements, should beunderstood to mean at least one element selected from any one or more ofthe elements in the list of elements, but not necessarily including atleast one of each and every element specifically listed within the listof elements and not excluding any combinations of elements in the listof elements. This definition also allows that elements may optionally bepresent other than the elements specifically identified within the listof elements to which the phrase “at least one” refers, whether relatedor unrelated to those elements specifically identified. Thus, forexample, “at least one of A and B” (or, equivalently, “at least one of Aor B,” or, equivalently “at least one of A and/or B”) can refer, in oneembodiment, to at least one, optionally including more than one, A, withno B present (and optionally including elements other than B); inanother embodiment, to at least one, optionally including more than one,B, with no A present (and optionally including elements other than A);in yet another embodiment, to at least one, optionally including morethan one, A, and at least one, optionally including more than one, B(and optionally including other elements); etc.

The phrase “and/or,” as used herein in the specification and in theclaims, should be understood to mean “either or both” of the elements soconjoined, i.e., elements that are conjunctively present in some casesand disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined. Other elements may optionally be presentother than the elements specifically identified by the “and/or” clause,whether related or unrelated to those elements specifically identified.Thus, as an example, a reference to “A and/or B”, when used inconjunction with open-ended language such as “comprising” can refer, inone embodiment, to A only (optionally including elements other than B);in another embodiment, to B only (optionally including elements otherthan A); in yet another embodiment, to both A and B (optionallyincluding other elements); etc.

In the claims articles such as “a,” “an,” and “the” may mean one or morethan one unless indicated to the contrary or otherwise evident from thecontext. Claims or descriptions that include “or” between one or moremembers of a group are considered satisfied if one, more than one, orall of the group members are present in, employed in, or otherwiserelevant to a given product or process unless indicated to the contraryor otherwise evident from the context. The disclosure includesembodiments in which exactly one member of the group is present in,employed in, or otherwise relevant to a given product or process. Thedisclosure includes embodiments in which more than one, or all of thegroup members are present in, employed in, or otherwise relevant to agiven product or process.

Furthermore, the described methods and systems encompass all variations,combinations, and permutations in which one or more limitations,elements, clauses, and descriptive terms from one or more of the listedclaims is introduced into another claim. For example, any claim that isdependent on another claim can be modified to include one or morelimitations found in any other claim that is dependent on the same baseclaim. Where elements are presented as lists, e.g., in Markush groupformat, each subgroup of the elements is also disclosed, and anyelement(s) can be removed from the group. It should it be understoodthat, in general, where the systems and methods described herein (oraspects thereof) are referred to as comprising particular elementsand/or features, certain embodiments of the systems and methods oraspects of the same consist, or consist essentially of, such elementsand/or features. For purposes of simplicity, those embodiments have notbeen specifically set forth in haec verba herein.

It is also noted that the terms “including,” “comprising,” “having,”“containing”, “involving”, are intended to be open and permits theinclusion of additional elements or steps. Where ranges are given,endpoints are included. Furthermore, unless otherwise indicated orotherwise evident from the context and understanding of one of ordinaryskill in the art, values that are expressed as ranges can assume anyspecific value or sub-range within the stated ranges in differentembodiments of the described systems and methods, to the tenth of theunit of the lower limit of the range, unless the context clearlydictates otherwise. The term “consisting” or phrase “consisting of” areintended to be closed terms and do not permit the inclusion ofadditional elements. Embodiments described as “comprising” an elementalso contemplate alternative embodiments “consisting of” such an elementor elements.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another or thetemporal order in which acts of a method are performed. Such terms areused merely as labels to distinguish one claim element having a certainname from another element having a same name (but for use of the ordinalterm).

Additionally, as used herein the terms “patient” and “subject” may beused interchangeably. Such terms may include, but are not limited to,human subjects or patients. Such terms may also include non-humanprimates or other animals.

This application refers to various issued patents, published patentapplications, journal articles, and other publications, all of which areincorporated herein by reference. If there is a conflict between any ofthe incorporated references and the instant specification, thespecification shall control. In addition, any particular embodiment ofthe present disclosure that fall within the prior art may be explicitlyexcluded from any one or more of the claims. Because such embodimentsare deemed to be known to one of ordinary skill in the art, they may beexcluded even if the exclusion is not set forth explicitly herein. Anyparticular embodiment of the systems and methods described herein can beexcluded from any claim, for any reason, whether or not related to theexistence of prior art.

Those skilled in the art will recognize or be able to ascertain using nomore than routine experimentation many equivalents to the specificembodiments described herein. The scope of the present embodimentsdescribed herein is not intended to be limited to the above Description,but rather is as set forth in the appended claims. Those of ordinaryskill in the art will appreciate that various changes and modificationsto this description may be made without departing from the spirit orscope of the present disclosure, as defined in the following claims.

1-30. (canceled)
 31. A method for determining a Diffuse Large B celllymphoma (DLBCL) microenvironment (LME) type of a subject, the methodcomprising: using at least one computer hardware processor to perform:obtaining at least 5 kb of sequencing data for a subject having,suspected of having, or at risk of having a DLBCL; determining a LMEsignature for the subject using the sequencing data, wherein thesequencing data comprises RNA expression data indicating RNA expressionlevels of each of the following genes in each of the following genegroups: (a) Lymphatic endothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN,CXADR, FLT4, CCL21, FOXC2, EDNRB, LYVE1, PROX1, SOX18, and JAM2; (b)Angiogenesis (VEC): CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2,ANGPT1, CXCL5, FLT1, VEGFA, KDR, VEGFB, and ANGPT2; (c)Cancer-associated fibroblasts (CAF): COL1A1, MMP2, LGALS1, MMP1, LRP1,CD248, S100A4, FAP, FGF2, MMP9, CTGF, ACTA2, FN1, COL1A2, COL5A1,COL6A1, MMP3, CA9, PRELP, FBLN1, COL6A3, COL11A1, TGFB3, MMP12, MFAP5,MMP1, COL6A2, TIMP1, COMA1, TGFB1, LUM, LGALS9, PTGS2, and TGFB2; (d)Fibroblastic reticular cells (FRC): PDGFRA, ACTA2, ICAM1, NT5E, VIM,PDPN, THY1, DES, VCAM1, PTGS2, and LTBR; (e) Matrix (ECM): COL1A1,COL3A1, LGALS7, FN1, VTN, COL1A2, and COMA1; (f) Matrix Remodeling (ECMremodeling): TIMP1, TIMP2, MMP2, MMP9, and CA9; (g) Granulocyte traffic:KITLG, CXCL8, CXCR1, CXCR2, CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2;(h) Protumor cytokines (IS cytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8,IL22, and IL10; (i) Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A,LTBR, FDCSP, CLU, PRNP, and BST1; (j) Macrophages: IL10, MSR1, ARG1,CSF1R, CD163, MRC1, and CSF1; (k) M1 signature (activated M1): TNF,NOS2, IL1B, and CMKLR1; (l) Effector cell traffic (T cell traffic):CXCL11, CXCL10, CXCL9, CXCR3, CX3CL1, CCL5, and CX3CR1; (m) Majorhistocompatibility complex II (MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1,HLA-DRA, HLA-DQA1, HLA-DMA, HLA-DRB1, and HLA-DMB; (n) Majorhistocompatibility complex I (MHC-I): TAP1, HLA-C, B2M, HLA-B, HLA-A,and TAP2; (o) Follicular B helper T cells (TFH): CD40LG, SH2D1A, CD84,CXCR5, IL4, IL6, MAF, BCL6, IL21, and ICOS; (p) Regulatory T cells(Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3, IL10, and TNFRSF18; (q) Tcells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK, CD28, CD3E, TRBC1, TRAC,and CD3G; (r) Checkpoint inhibition (IS checkpoints): CTLA4, HAVCR2,CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, and LAG3; (s) Natural Killer Cells(NK cells): SH2D1B, GZMH, GZMB, CD160, KLRK1, NCR3, CD244, IFNG, GNLY,NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2, KIR2DL4, and KLRF1; (t) B celltraffic: CXCL13, CXCR5, CCR6, and CCL20; (u) Benign B cells (B cells):CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22, TNFRSF13B, BLK, CD19, PAX5,CD79A, TNFRSF13C, and FCRL5; and (v) Tumor proliferation rate (cellproliferation): MCM6, AURKB, ESCO2, CCNB1, AURKA, MKI67, CCND1, CCNE1,MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, and BUB1, and wherein the LMEsignature comprises: (i) a gene expression signature comprising aplurality of gene group expression scores, wherein the gene groupexpression scores are produced by performing gene set enrichmentanalysis (GSEA) using the RNA expression levels for each of thefollowing genes in each of the following gene groups: (a) Lymphaticendothelium (LEC): JAM3, PPP1R13B, CXCL12, PDPN, CXADR, FLT4, CCL21,FOXC2, EDNRB, LYVE1, PROX1, SOX18, and JAM2; (b) Angiogenesis (VEC):CDH5, PGF, PDGFC, TEK, VEGFC, CXCL8, VWF, CXCR2, ANGPT1, CXCL5, FLT1,VEGFA, KDR, VEGFB, and ANGPT2; (c) Cancer-associated fibroblasts (CAF):COL1A1, MMP2, LGALS1, MMP1, LRP1, CD248, S100A4, FAP, FGF2, MMP9, CTGF,ACTA2, FN1, COL1A2, COL5A1, COL6A1, MMP3, CA9, PRELP, FBLN1, COL6A3,COL11A1, TGFB3, MMP12, MFAP5, MMP1, COL6A2, TIMP1, COL4A1, TGFB1, LUM,LGALS9, PTGS2, and TGFB2; (d) Fibroblastic reticular cells (FRC):PDGFRA, ACTA2, ICAM1, NT5E, VIM, PDPN, THY1, DES, VCAM1, PTGS2, andLTBR; (e) Matrix (ECM): COL1A1, COL3A1, LGALS7, FN1, VTN, COL1A2, andCOL4A1; (f) Matrix Remodeling (ECM remodeling): TIMP1, TIMP2, MMP2,MMP9, and CA9; (g) Granulocyte traffic: KITLG, CXCL8, CXCR1, CXCR2,CXCL5, KIT, CCL11, CCR3, CXCL1, and CXCL2; (h) Protumor cytokines (IScytokines): CCL4, IL6, TNFSF13B, MIF, CXCL8, IL22, and IL10; (i)Follicular Dendritic Cells (FDC): PDPN, TNFRSF1A, LTBR, FDCSP, CLU,PRNP, and BST1; (j) Macrophages: IL10, MSR1, ARG1, CSF1R, CD163, MRC1,and CSF1; (k) M1 signature (activated M1): TNF, NOS2, IL1B, and CMKLR1;(l) Effector cell traffic (T cell traffic): CXCL11, CXCL10, CXCL9,CXCR3, CX3CL1, CCL5, and CX3CR1; (m) Major histocompatibility complex II(MHC-II): HLA-DQB1, HLA-DPB1, HLA-DPA1, HLA-DRA, HLA-DQA1, HLA-DMA,HLA-DRB1, and HLA-DMB; (n) Major histocompatibility complex I (MHC-I):TAP1, HLA-C, B2M, HLA-B, HLA-A, and TAP2; (o) Follicular B helper Tcells (TFH): CD40LG, SH2D1A, CD84, CXCR5, IL4, IL6, MAF, BCL6, IL21, andICOS; (p) Regulatory T cells (Treg): CCR8, CTLA4, IKZF2, IKZF4, FOXP3,IL10, and TNFRSF18; (q) T cells (TIL): CD3D, TRAT1, TBX21, TRBC2, ITK,CD28, CD3E, TRBC1, TRAC, and CD3G; (r) Checkpoint inhibition (IScheckpoints): CTLA4, HAVCR2, CD274, PDCD1, BTLA, TIGIT, PDCD1LG2, andLAG3; (s) Natural Killer Cells (NK cells): SH2D1B, GZMH, GZMB, CD160,KLRK1, NCR3, CD244, IFNG, GNLY, NCR1, CD226, NKG7, EOMES, KLRC2, FGFBP2,KIR2DL4, and KLRF1; (t) B cell traffic: CXCL13, CXCR5, CCR6, and CCL20;(u) Benign B cells (B cells): CD79B, MS4A1, STAP1, TNFRSF17, CD24, CD22,TNFRSF13B, BLK, CD19, PAX5, CD79A, TNFRSF13C, and FCRL5; and (v) Tumorproliferation rate (cell proliferation): MCM6, AURKB, ESCO2, CCNB1,AURKA, MKI67, CCND1, CCNE1, MCM2, MYBL2, E2F1, CETN3, CDK2, PLK1, andBUB1; and (ii) one or more PROGENY pathway scores for the sequencingdata, wherein the one or more PROGENY pathway scores are selected fromNuclear factor kappa B (NFkB), Phosphoinositide 3-kinase (PI3K), andp53; and assigning, from a plurality of LME types comprising LME-A type,LME-B type, LME-C type, and LME-D type, an LME type A (LME-A) to thesubject using the LME signature, wherein the LME type A subjectcomprises increased levels of MMP9, MMP2, TIMP1 and TIMP2; wherein theassigning comprises associating the LME signature of the subject with acluster of previously determined LME signatures selected from a LME-Atype cluster, LME-B type cluster, LME-C type cluster, and LME-D typecluster; and administering an immunotherapy to the subject assigned ashaving an LME-A type.
 32. The method of claim 31, further comprisingidentifying the subject as having a decreased chance of a PFS24 eventrelative to other LME types when the subject is assigned type LME-A. 33.The method of claim 31, wherein the method further comprises obtainingan International Prognostic Index (IPI) score of the subject, whereinthe IPI score is Low, Intermediate, or High.
 34. The method of claim 33,further comprising identifying the subject as having an increased chanceof a PFS24 event relative to other LME types when the DLBCL is typeLME-A ABC and the IPI score is Intermediate.
 35. The method of claim 31,wherein the immunotherapy comprises an immune checkpoint inhibitor. 36.The method of claim 35, wherein the immune checkpoint inhibitorcomprises a PD1 inhibitor, PD-L1 inhibitor, or CTLA-4 inhibitor.
 37. Themethod of claim 35, wherein the immune checkpoint inhibitor is anantibody.